22 Data Science Intern jobs in Qatar

SWATX is seeking a highly skilled and experienced Data Science Manager to lead our growing data science team. In this strategic role, you will be responsible for overseeing the development and implementation of data-driven solutions to solve complex business challenges. You will mentor and guide a team of data scientists, driving innovation and excellence in analytics and machine learning. If you are a strong leader with a passion for data science and a proven track record of delivering impactful solutions, we invite you to join us.

Responsibilities:

• Lead and mentor a team of data scientists, providing guidance on best practices in data analysis, machine learning, and statistical modeling
• Develop and execute the data science strategy aligned with business objectives, ensuring that data-driven insights are integrated into decision-making processes
• Oversee the design and implementation of innovative data science projects that drive value for the organization
• Collaborate with cross-functional teams to identify opportunities for leveraging data to improve products, services, and operational efficiency
• Build and maintain strong relationships with stakeholders, understanding their data needs and ensuring timely delivery of insights
• Monitor and evaluate the performance of data science models and adjust strategies as necessary to achieve desired results
• Promote a data-driven culture within the organization by communicating the value of data science initiatives to stakeholders at all levels
• Stay updated on the latest trends and developments in data science and analytics, and integrate new methodologies and tools as appropriate
  
  

Requirements

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
• Proven experience in a data science role, with at least 5+ years of experience, including 2+ years in a managerial or leadership position
• Strong proficiency in programming languages such as Python, R, and experience with data manipulation and analysis libraries
• Solid understanding of machine learning algorithms, statistical methodologies, and data modeling techniques
• Experience with data visualization tools (e.g., Tableau, Power BI) to communicate findings effectively
• Excellent project management skills and ability to prioritize tasks in a fast-paced environment
• Strong analytical and problem-solving skills with attention to detail
• Exceptional communication skills, both verbal and written, in English and Arabic
• Proven capability to drive collaboration across teams and influence senior stakeholders
  
  

Preferable Certificates:

• Certified Data Scientist (CDS)
• Microsoft Certified: Azure Data Scientist Associate
• Google Cloud Professional Data Engineer

#J-18808-Ljbffr

SWATX is seeking a highly skilled and experienced Data Science Manager to lead our growing data science team. In this strategic role, you will be responsible for overseeing the development and implementation of data-driven solutions to solve complex business challenges. You will mentor and guide a team of data scientists, driving innovation and excellence in analytics and machine learning. If you are a strong leader with a passion for data science and a proven track record of delivering impactful solutions, we invite you to join us.

Responsibilities:

Lead and mentor a team of data scientists, providing guidance on best practices in data analysis, machine learning, and statistical modeling Develop and execute the data science strategy aligned with business objectives, ensuring that data-driven insights are integrated into decision-making processes Oversee the design and implementation of innovative data science projects that drive value for the organization Collaborate with cross-functional teams to identify opportunities for leveraging data to improve products, services, and operational efficiency Build and maintain strong relationships with stakeholders, understanding their data needs and ensuring timely delivery of insights Monitor and evaluate the performance of data science models and adjust strategies as necessary to achieve desired results Promote a data-driven culture within the organization by communicating the value of data science initiatives to stakeholders at all levels Stay updated on the latest trends and developments in data science and analytics, and integrate new methodologies and tools as appropriate

Requirements

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field Proven experience in a data science role, with at least 5+ years of experience, including 2+ years in a managerial or leadership position Strong proficiency in programming languages such as Python, R, and experience with data manipulation and analysis libraries Solid understanding of machine learning algorithms, statistical methodologies, and data modeling techniques Experience with data visualization tools (e.g., Tableau, Power BI) to communicate findings effectively Excellent project management skills and ability to prioritize tasks in a fast-paced environment Strong analytical and problem-solving skills with attention to detail Exceptional communication skills, both verbal and written, in English and Arabic Proven capability to drive collaboration across teams and influence senior stakeholders

Preferable Certificates:

Certified Data Scientist (CDS) Microsoft Certified: Azure Data Scientist Associate Google Cloud Professional Data Engineer

#J-18808-Ljbffr

SWATX is looking for a visionary and results-driven Senior Data Science Manager to join our leadership team. In this pivotal role, you will be responsible for overseeing the strategic direction and execution of data science initiatives across the organization. You will lead a talented team of data scientists, driving innovation in predictive modeling, machine learning, and advanced analytics. As a key contributor to our data strategy, you will collaborate closely with senior leadership and cross-functional teams to deliver impactful insights and solutions that enhance business performance.

Responsibilities:

1. Develop and implement the overall data science vision, strategy, and framework to align with organizational goals.
2. Lead a high-performing team of data scientists, fostering a culture of collaboration, innovation, and continuous learning.
3. Drive the execution of strategic data science projects, ensuring alignment with business objectives and delivery of actionable insights.
4. Collaborate with stakeholders to identify high-impact opportunities for modeling and analytics that can enhance decision-making and operational efficiency.
5. Oversee the design and implementation of complex machine learning algorithms and statistical models to solve business challenges.
6. Monitor industry trends and emerging technologies in data science and analytics, incorporating best practices into the team's methodologies.
7. Provide mentorship and professional development opportunities for team members to enhance their skill sets and career growth.
8. Present findings and recommendations to senior leadership, translating complex data insights into clear and actionable strategies.

SWATX is looking for a visionary and results-driven Senior Data Science Manager to join our leadership team. In this pivotal role, you will be responsible for overseeing the strategic direction and execution of data science initiatives across the organization. You will lead a talented team of data scientists, driving innovation in predictive modeling, machine learning, and advanced analytics. As a key contributor to our data strategy, you will collaborate closely with senior leadership and cross-functional teams to deliver impactful insights and solutions that enhance business performance.

Responsibilities:

1. Develop and implement the overall data science vision, strategy, and framework to align with organizational goals.
2. Lead a high-performing team of data scientists, fostering a culture of collaboration, innovation, and continuous learning.
3. Drive the execution of strategic data science projects, ensuring alignment with business objectives and delivery of actionable insights.
4. Collaborate with stakeholders to identify high-impact opportunities for modeling and analytics that can enhance decision-making and operational efficiency.
5. Oversee the design and implementation of complex machine learning algorithms and statistical models to solve business challenges.
6. Monitor industry trends and emerging technologies in data science and analytics, incorporating best practices into the team’s methodologies.
7. Provide mentorship and professional development opportunities for team members to enhance their skill sets and career growth.
8. Present findings and recommendations to senior leadership, translating complex data insights into clear and actionable strategies.

#J-18808-Ljbffr

SWATX is looking for a visionary and results-driven Senior Data Science Manager to join our leadership team. In this pivotal role, you will be responsible for overseeing the strategic direction and execution of data science initiatives across the organization. You will lead a talented team of data scientists, driving innovation in predictive modeling, machine learning, and advanced analytics. As a key contributor to our data strategy, you will collaborate closely with senior leadership and cross-functional teams to deliver impactful insights and solutions that enhance business performance.

Responsibilities: Develop and implement the overall data science vision, strategy, and framework to align with organizational goals. Lead a high-performing team of data scientists, fostering a culture of collaboration, innovation, and continuous learning. Drive the execution of strategic data science projects, ensuring alignment with business objectives and delivery of actionable insights. Collaborate with stakeholders to identify high-impact opportunities for modeling and analytics that can enhance decision-making and operational efficiency. Oversee the design and implementation of complex machine learning algorithms and statistical models to solve business challenges. Monitor industry trends and emerging technologies in data science and analytics, incorporating best practices into the team’s methodologies. Provide mentorship and professional development opportunities for team members to enhance their skill sets and career growth. Present findings and recommendations to senior leadership, translating complex data insights into clear and actionable strategies.

#J-18808-Ljbffr

About QNB

Established in 1964 as the countrys first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region.

QNB Groups presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines.

QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poors (A), Moodys (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications.

Based on the Groups consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine.

QNB Group has an active community support program and sponsors various social, educational and sporting events.

Job Summary

The Senior Vice President (SVP), Data Science, is a strategic leadership role responsible for shaping, leading, and executing QNB&aposs bank-wide Data & AI strategy. This position drives innovation and transformation across the bank using advanced data analytics, machine learning, deep learning, and Generative AI (GenAI). The SVP works closely with executive stakeholders to align data science initiatives with business priorities, ensure strong governance, and build scalable AI capabilities that drive financial performance, operational efficiency, and superior customer experiences. The role also includes oversight of Advanced Analytics, AI model lifecycle management, talent development, and the promotion of ethical Data & AI use across QNB.

Main Responsibilities

• Shareholder & Financial:
• Define and drive execution of QNB&aposs enterprise Data Science & AI strategy aligned to business outcomes.
• Deliver high-impact, AI-powered solutions that generate measurable financial benefits (e.g., revenue growth, cost efficiency, risk mitigation).
• Oversee budgeting and resource allocation across strategic data initiatives.
• Monitor the ROI of Data Science & AI investments using business-focused KPIs and OKRs.
• Establish a data-driven culture across the bank, ensuring AI is embedded in all relevant decision-making processes.
• Implements KPIs and best practices for Senior Vice President, Data Science
• Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank.
• Act within the limits of the powers delegated to the incumbent and delegate authority to the respective staff and monitor exercise of the same.
• Demonstrate clear understanding of the important factors behind the bank&aposs financial & non-financial performance.
• Customer (Internal & External):
• Partner with Group business Heads and IT to develop AI solutions that enhance customer engagement, improve
  
  

product personalization, and streamline operations.

• Provide thought leadership on the application of GenAI, advanced analytics, and predictive models for business growth.
• Translate complex data science approaches into business-ready narratives for CXOs and Board-level communication.
• Lead AI capability-building programs for business units, enabling self-serve analytics and citizen data science.
• Champion customer-centric design in all AI and data-driven solutions.
• To assist customers in all their queries on Banks product and seek solution to their requests.
• Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time.
• Build and maintain strong/effective relationships with related departments/units to achieve the Groups objectives.
• Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required.
• Internal (Processes, Products, Regulatory):
• Establish scalable AI & ML development pipelines including robust model governance, MLOps, and monitoring frameworks.
• Oversee the development of AI models across use cases such as credit risk, client profitability, fraud detection, customer acquisition, and treasury optimization.
• Ensure compliance with internal and external data protection, governance, and regulatory standards.
• Build and institutionalize reusable data products and GenAI agents across business functions.
• Drive innovation in data science practices by integrating cloud-native platforms, LLMs, and enterprise AI tools.
• Continuous Improvement:
• Set examples by leading improvement initiatives through cross-functional teams ensuring successes.
• Identify and encourage people to adopt practices better than the industry standard.
• Continuously encourage and recognise the importance of thinking out-of-the-box within the team.
• Encourage, solicit and reward innovative ideas even in day-to-day issues.
• Learning & Knowledge:
• Lead a high-performing Data Science & AI team, fostering a culture of experimentation, continuous learning, and ethical AI usage.
• Institutionalize knowledge-sharing platforms and AI Centers of Excellence (CoEs).
• Stay abreast of global AI trends, regulatory developments, and advancements in GenAI, LLMs, and deep learning.
• Collaborate with academia, research bodies, and vendors to infuse cutting-edge knowledge into QNB.
• Proactively identify areas for professional development of self and undertake development activities.
• Seek out opportunities to stay current with advancements in AI and data analytics fields.
• Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects.
• Hold meetings with staff and assess their performance and your teams overall performance on a regular basis.
• Take decisive action to ensure speedy resolution of unresolved grievances or conflicts within the team members.
• Identify development opportunities and activities for staff and facilitate/coach them to improve their effectives and prepare them to assume greater responsibilities.
• Legal, Regulatory, and Risk Framework Responsibilities:
• Ensure adherence to all AI-related legal, ethical, and compliance frameworks including AI governance, data privacy, and explainability standards.
• Represent Data Science & AI in Operational Risk, Compliance, and Board-level risk reviews.
• Lead remediation planning for model risk, bias detection, and audit compliance.
• Maintain AI documentation in line with regulatory expectations, particularly for credit, fraud, AML, and client fairness.
• Complete all mandatory training provided by the organization to achieve and maintain the required levels of competence in data science, analytics, and AI fields.
• Attend all required (internal and external) seminars and workshops, as instructed, to stay abreast of the latest advancements and best practices in data analytics and AI.
• Other:
• Ensure high standards of data protection and confidentiality to safeguard all data and systems.
• Maintaining utmost confidentiality concerning customer data and internal information obtained during the course of business and provide such information on a need-to-know basis only to Senior Management, Audit and Compliance functions, and relevant Regulators.
• Maintain high professional standards to uphold the organization&aposs reputation and to strengthen its leadership position in data analytics and AI.
• All other ad hoc duties/activities related to data analytics and AI that management might request from time to time
  
  

Education And Experience Requirements

• Masters or PhD in Data Science, Computer Science, AI, Engineering, Statistics, or related quantitative field.
• Minimum 15 years of total experience, with at least 10 years in data analytics, data science, or AI leadership roles.
• Proven experience leading AI transformation programs in banking or financial services.
• Deep expertise in AI/ML techniques including LLMs, deep learning, predictive analytics, GenAI, and NLP.
• Strong track record of building and scaling AI teams and delivering enterprise-grade AI solutions.
• Solid knowledge of financial products, customer analytics, credit scoring, risk modeling, and regulatory AI applications.
• Hands-on experience with cloud ecosystems (Azure, AWS, GCP), modern data stacks, and production-grade ML/AI platforms.
• Strong stakeholder management and strategic execution and advisory skills.
• Ability to design AI governance frameworks aligned with regulatory and ethical standards.
• Advanced skills in Python, Spark, SQL, cloud-based ML pipelines, MLOps, and LLM deployment.
• Familiarity with tools like Databricks, Azure AI, Dataiku, and enterprise GenAI platforms.
• Clear communication of complex data science topics to non-technical audiences.
• Demonstrated innovation mindset with bias for action and delivery.
  
  

Note: you will be required to attach the following:

• Resume/CV
• Copy of Passport or QID
• Copy of Education Certificate

Show more Show less

About QNB

Established in 1964 as the countrys first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region.

QNB Groups presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines.

QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poors (A), Moodys (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications.

Based on the Groups consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine.

QNB Group has an active community support program and sponsors various social, educational and sporting events.

Job Summary

The Senior Vice President (SVP), Data Science, is a strategic leadership role responsible for shaping, leading, and executing QNB&aposs bank-wide Data & AI strategy. This position drives innovation and transformation across the bank using advanced data analytics, machine learning, deep learning, and Generative AI (GenAI). The SVP works closely with executive stakeholders to align data science initiatives with business priorities, ensure strong governance, and build scalable AI capabilities that drive financial performance, operational efficiency, and superior customer experiences. The role also includes oversight of Advanced Analytics, AI model lifecycle management, talent development, and the promotion of ethical Data & AI use across QNB.

Main Responsibilities

• Shareholder & Financial:
• Define and drive execution of QNB&aposs enterprise Data Science & AI strategy aligned to business outcomes.
• Deliver high-impact, AI-powered solutions that generate measurable financial benefits (e.g., revenue growth, cost efficiency, risk mitigation).
• Oversee budgeting and resource allocation across strategic data initiatives.
• Monitor the ROI of Data Science & AI investments using business-focused KPIs and OKRs.
• Establish a data-driven culture across the bank, ensuring AI is embedded in all relevant decision-making processes.
• Implements KPIs and best practices for Senior Vice President, Data Science
• Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank.
• Act within the limits of the powers delegated to the incumbent and delegate authority to the respective staff and monitor exercise of the same.
• Demonstrate clear understanding of the important factors behind the bank&aposs financial & non-financial performance.
• Customer (Internal & External):
• Partner with Group business Heads and IT to develop AI solutions that enhance customer engagement, improve
  
  

product personalization, and streamline operations.

• Provide thought leadership on the application of GenAI, advanced analytics, and predictive models for business growth.
• Translate complex data science approaches into business-ready narratives for CXOs and Board-level communication.
• Lead AI capability-building programs for business units, enabling self-serve analytics and citizen data science.
• Champion customer-centric design in all AI and data-driven solutions.
• To assist customers in all their queries on Banks product and seek solution to their requests.
• Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time.
• Build and maintain strong/effective relationships with related departments/units to achieve the Groups objectives.
• Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required.
• Internal (Processes, Products, Regulatory):
• Establish scalable AI & ML development pipelines including robust model governance, MLOps, and monitoring frameworks.
• Oversee the development of AI models across use cases such as credit risk, client profitability, fraud detection, customer acquisition, and treasury optimization.
• Ensure compliance with internal and external data protection, governance, and regulatory standards.
• Build and institutionalize reusable data products and GenAI agents across business functions.
• Drive innovation in data science practices by integrating cloud-native platforms, LLMs, and enterprise AI tools.
• Continuous Improvement:
• Set examples by leading improvement initiatives through cross-functional teams ensuring successes.
• Identify and encourage people to adopt practices better than the industry standard.
• Continuously encourage and recognise the importance of thinking out-of-the-box within the team.
• Encourage, solicit and reward innovative ideas even in day-to-day issues.
• Learning & Knowledge:
• Lead a high-performing Data Science & AI team, fostering a culture of experimentation, continuous learning, and ethical AI usage.
• Institutionalize knowledge-sharing platforms and AI Centers of Excellence (CoEs).
• Stay abreast of global AI trends, regulatory developments, and advancements in GenAI, LLMs, and deep learning.
• Collaborate with academia, research bodies, and vendors to infuse cutting-edge knowledge into QNB.
• Proactively identify areas for professional development of self and undertake development activities.
• Seek out opportunities to stay current with advancements in AI and data analytics fields.
• Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects.
• Hold meetings with staff and assess their performance and your teams overall performance on a regular basis.
• Take decisive action to ensure speedy resolution of unresolved grievances or conflicts within the team members.
• Identify development opportunities and activities for staff and facilitate/coach them to improve their effectives and prepare them to assume greater responsibilities.
• Legal, Regulatory, and Risk Framework Responsibilities:
• Ensure adherence to all AI-related legal, ethical, and compliance frameworks including AI governance, data privacy, and explainability standards.
• Represent Data Science & AI in Operational Risk, Compliance, and Board-level risk reviews.
• Lead remediation planning for model risk, bias detection, and audit compliance.
• Maintain AI documentation in line with regulatory expectations, particularly for credit, fraud, AML, and client fairness.
• Complete all mandatory training provided by the organization to achieve and maintain the required levels of competence in data science, analytics, and AI fields.
• Attend all required (internal and external) seminars and workshops, as instructed, to stay abreast of the latest advancements and best practices in data analytics and AI.
• Other:
• Ensure high standards of data protection and confidentiality to safeguard all data and systems.
• Maintaining utmost confidentiality concerning customer data and internal information obtained during the course of business and provide such information on a need-to-know basis only to Senior Management, Audit and Compliance functions, and relevant Regulators.
• Maintain high professional standards to uphold the organization&aposs reputation and to strengthen its leadership position in data analytics and AI.
• All other ad hoc duties/activities related to data analytics and AI that management might request from time to time
  
  

Education And Experience Requirements

• Masters or PhD in Data Science, Computer Science, AI, Engineering, Statistics, or related quantitative field.
• Minimum 15 years of total experience, with at least 10 years in data analytics, data science, or AI leadership roles.
• Proven experience leading AI transformation programs in banking or financial services.
• Deep expertise in AI/ML techniques including LLMs, deep learning, predictive analytics, GenAI, and NLP.
• Strong track record of building and scaling AI teams and delivering enterprise-grade AI solutions.
• Solid knowledge of financial products, customer analytics, credit scoring, risk modeling, and regulatory AI applications.
• Hands-on experience with cloud ecosystems (Azure, AWS, GCP), modern data stacks, and production-grade ML/AI platforms.
• Strong stakeholder management and strategic execution and advisory skills.
• Ability to design AI governance frameworks aligned with regulatory and ethical standards.
• Advanced skills in Python, Spark, SQL, cloud-based ML pipelines, MLOps, and LLM deployment.
• Familiarity with tools like Databricks, Azure AI, Dataiku, and enterprise GenAI platforms.
• Clear communication of complex data science topics to non-technical audiences.
• Demonstrated innovation mindset with bias for action and delivery.
  
  

Note: you will be required to attach the following:

• Resume/CV
• Copy of Passport or QID
• Copy of Education Certificate

#J-18808-Ljbffr

About QNB

Established in 1964 as the countrys first Qatari-owned commercial bank, QNB Group has steadily grown to become the largest bank in the Middle East and Africa (MEA) region.

QNB Groups presence through its subsidiaries and associate companies extends to more than 31 countries across three continents providing a comprehensive range of advanced products and services. The total number of employees is more than 28,000 serving up to 20 million customers operating through 1,000 locations, with an ATM network of 4,300 machines.

QNB has maintained its position as one of the highest rated regional banks from leading credit rating agencies including Standard & Poors (A), Moodys (Aa3) and Fitch (A+). The Bank has also been the recipient of many awards from leading international specialised financial publications.

Based on the Groups consistent strong financial performance and its expanding international presence, QNB currently ranks as the most valuable bank brand in the Middle East and Africa, according to Brand Finance Magazine.

QNB Group has an active community support program and sponsors various social, educational and sporting events.

Job Summary

The Senior Vice President (SVP), Data Science, is a strategic leadership role responsible for shaping, leading, and executing QNB&aposs bank-wide Data & AI strategy. This position drives innovation and transformation across the bank using advanced data analytics, machine learning, deep learning, and Generative AI (GenAI). The SVP works closely with executive stakeholders to align data science initiatives with business priorities, ensure strong governance, and build scalable AI capabilities that drive financial performance, operational efficiency, and superior customer experiences. The role also includes oversight of Advanced Analytics, AI model lifecycle management, talent development, and the promotion of ethical Data & AI use across QNB.

Main Responsibilities

Shareholder & Financial: Define and drive execution of QNB&aposs enterprise Data Science & AI strategy aligned to business outcomes. Deliver high-impact, AI-powered solutions that generate measurable financial benefits (e.g., revenue growth, cost efficiency, risk mitigation). Oversee budgeting and resource allocation across strategic data initiatives. Monitor the ROI of Data Science & AI investments using business-focused KPIs and OKRs. Establish a data-driven culture across the bank, ensuring AI is embedded in all relevant decision-making processes. Implements KPIs and best practices for Senior Vice President, Data Science Promote cost consciousness and efficiency and enhance productivity, to minimise cost, avoid waste, and optimise benefits for the bank. Act within the limits of the powers delegated to the incumbent and delegate authority to the respective staff and monitor exercise of the same. Demonstrate clear understanding of the important factors behind the bank&aposs financial & non-financial performance. Customer (Internal & External): Partner with Group business Heads and IT to develop AI solutions that enhance customer engagement, improve

product personalization, and streamline operations.

Provide thought leadership on the application of GenAI, advanced analytics, and predictive models for business growth. Translate complex data science approaches into business-ready narratives for CXOs and Board-level communication. Lead AI capability-building programs for business units, enabling self-serve analytics and citizen data science. Champion customer-centric design in all AI and data-driven solutions. To assist customers in all their queries on Banks product and seek solution to their requests. Maintain activities in accordance with Service Level Agreements (SLAs) with internal departments/units to achieve improvements in turn-around time. Build and maintain strong/effective relationships with related departments/units to achieve the Groups objectives. Provide timely/accurate data to external/internal Auditors, Compliance, Financial Control and Risk when required. Internal (Processes, Products, Regulatory): Establish scalable AI & ML development pipelines including robust model governance, MLOps, and monitoring frameworks. Oversee the development of AI models across use cases such as credit risk, client profitability, fraud detection, customer acquisition, and treasury optimization. Ensure compliance with internal and external data protection, governance, and regulatory standards. Build and institutionalize reusable data products and GenAI agents across business functions. Drive innovation in data science practices by integrating cloud-native platforms, LLMs, and enterprise AI tools. Continuous Improvement: Set examples by leading improvement initiatives through cross-functional teams ensuring successes. Identify and encourage people to adopt practices better than the industry standard. Continuously encourage and recognise the importance of thinking out-of-the-box within the team. Encourage, solicit and reward innovative ideas even in day-to-day issues. Learning & Knowledge: Lead a high-performing Data Science & AI team, fostering a culture of experimentation, continuous learning, and ethical AI usage. Institutionalize knowledge-sharing platforms and AI Centers of Excellence (CoEs). Stay abreast of global AI trends, regulatory developments, and advancements in GenAI, LLMs, and deep learning. Collaborate with academia, research bodies, and vendors to infuse cutting-edge knowledge into QNB. Proactively identify areas for professional development of self and undertake development activities. Seek out opportunities to stay current with advancements in AI and data analytics fields. Initiate regular meetings within the Application Development department focused on discussing progress, resolving issues, and addressing concerns related to AI and data analytics projects. Hold meetings with staff and assess their performance and your teams overall performance on a regular basis. Take decisive action to ensure speedy resolution of unresolved grievances or conflicts within the team members. Identify development opportunities and activities for staff and facilitate/coach them to improve their effectives and prepare them to assume greater responsibilities. Legal, Regulatory, and Risk Framework Responsibilities: Ensure adherence to all AI-related legal, ethical, and compliance frameworks including AI governance, data privacy, and explainability standards. Represent Data Science & AI in Operational Risk, Compliance, and Board-level risk reviews. Lead remediation planning for model risk, bias detection, and audit compliance. Maintain AI documentation in line with regulatory expectations, particularly for credit, fraud, AML, and client fairness. Complete all mandatory training provided by the organization to achieve and maintain the required levels of competence in data science, analytics, and AI fields. Attend all required (internal and external) seminars and workshops, as instructed, to stay abreast of the latest advancements and best practices in data analytics and AI. Other: Ensure high standards of data protection and confidentiality to safeguard all data and systems. Maintaining utmost confidentiality concerning customer data and internal information obtained during the course of business and provide such information on a need-to-know basis only to Senior Management, Audit and Compliance functions, and relevant Regulators. Maintain high professional standards to uphold the organization&aposs reputation and to strengthen its leadership position in data analytics and AI. All other ad hoc duties/activities related to data analytics and AI that management might request from time to time

Education And Experience Requirements

Masters or PhD in Data Science, Computer Science, AI, Engineering, Statistics, or related quantitative field. Minimum 15 years of total experience, with at least 10 years in data analytics, data science, or AI leadership roles. Proven experience leading AI transformation programs in banking or financial services. Deep expertise in AI/ML techniques including LLMs, deep learning, predictive analytics, GenAI, and NLP. Strong track record of building and scaling AI teams and delivering enterprise-grade AI solutions. Solid knowledge of financial products, customer analytics, credit scoring, risk modeling, and regulatory AI applications. Hands-on experience with cloud ecosystems (Azure, AWS, GCP), modern data stacks, and production-grade ML/AI platforms. Strong stakeholder management and strategic execution and advisory skills. Ability to design AI governance frameworks aligned with regulatory and ethical standards. Advanced skills in Python, Spark, SQL, cloud-based ML pipelines, MLOps, and LLM deployment. Familiarity with tools like Databricks, Azure AI, Dataiku, and enterprise GenAI platforms. Clear communication of complex data science topics to non-technical audiences. Demonstrated innovation mindset with bias for action and delivery.

Note: you will be required to attach the following:

Resume/CV Copy of Passport or QID Copy of Education Certificate Show more

Show less #J-18808-Ljbffr

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Assistant/ Associate Professor - Data Science and Artificial Intelligence

University of Doha for Science and Technology (UDST) was officially established by the Emiri Decision No13 of 2022, and it is the first national university specializing in academic applied, technical, and professional education in the State of Qatar. UDST has over 70 bacheloru2019s and masteru2019s degree programs, diplomas, and certificates. The university houses 5 colleges: The College of Business, the College of Computing and Information Technology, the College of Engineering and Technology, the College of Health Sciences, and the College of General Education, in addition to specialized training centers for individuals and companies. UDST is recognized for its student-centered learning and state-of-the-art facilities. Its world-renowned faculty and researchers work on developing the studentsu2019 skills and help raise well-equipped graduates who proudly serve different sectors of the economy and contribute to achieving human, social, and economic development goals nationally and internationally.

With more than 700 staff and over 8,000 students, UDST is the destination of choice for applied and experiential learning. The University is recognized for its student-centered learning and state-of-the-art facilities. Our faculty are committed to delivering pedagogically-sound learning experiences that incorporate innovative learning technologies. Our aim is to enhance studentsu2019 skills and help develop talented graduates who can effectively contribute to a knowledge-based economy and make Qataru2019s National Vision 2030 a reality.

Our eligible employees enjoy competitive compensation and benefits, in accordance with applicable UDST policies. These benefits include:

• Generous academic annual leave
• Tax free salary
• Fully furnished upmarket accommodation (inclusive of utilities: water & electricity)
• Annual flights for spouse and 3 children (up to 18 years old)
• Relocation/Shipping allowance
• International health insurance
• In-house immigration services (to help you through the residency process)
• Full access to our recreational facilities
• Research and professional development support

The College of Computing and Information Technology (CCIT) invites applications for the position of Assistant/Associate Professor in Data Science and Artificial Intelligence. Exceptional candidates at the rank of Full Professor would also be considered.

Your Commitment

The primary role of the faculty members at the College of Computing and IT is to promote high-quality applied learning, innovative research, and service. Besides, he/she should collaborate with the college management and the rest of faculty to achieve the collegeu2019s mission, deliver academic programs, pursue research, and engage in several administrative and academic services.

Reporting to the Department Head, the successful candidate will be responsible for the development, delivery and evaluation of a broad range of courses within Data Science and Artificial Intelligence. Particular areas of interest include Machine Learning, Deep Learning, Visualization and Intelligent Interaction, Industrial and Business Analytics, IoT Software and Systems, and IoT Intelligence and Automation, but candidates with strong expertise in other areas related to Data Science and Artificial Intelligence will also be considered. Other duties include evaluation of student progress and management of resources of the learning environment. The successful candidate will liaise with industry and other educational institutions; participate in industry advisory committees and coordinate, manage and control projects within the specified program area. Faculty members will keep course portfolio documents required for accreditation processes and engage in instructional development/improvement plans. All faculty are expected to contribute to professional and community life within the university and beyond.

Responsibilities

Education and Experience Requirements

Faculty members will be placed in the appropriate rank based on their education and experience (academic and/or industry). The broad criteria are provided below.

Education

PhD and a Masteru2019s degree in Data Science and Artificial Intelligence or closely related field from an internationally recognized university with an undergraduate degree from an accredited university.

Experience

A minimum of 3 years teaching experience in a post-secondary, adult training or industry training environment, along with preferably 3 years of employment experience as a practitioner/professional within the relevant discipline.

An active research agenda evidenced by high-quality publications in top tier journals and conference proceedings.

Demonstrated leadership in building engagement and partnership with the profession and industry.

Preferred Qualifications

Professional Certification in Data Science and Artificial Intelligence.

Diploma in Education (e.g., Post-secondary Education, Adult Education, and Vocational Education) is preferred.

6+ years of employment experience as a practitioner/professional within the relevant discipline.

Experience in leadership and innovation in technology-based projects.

For Associate Professor

Experience

A minimum of 8 years teaching experience in a post-secondary, adult training or industry training environment, along with preferably 3years of employment experience as a practitioner/professional within the relevant discipline.

A distinguished research record and international reputation evidenced by high quality publications in mainly top tier journals.

Excellent record of supervising research students.

Demonstrated leadership in building engagement and partnership with the profession and industry.

Preferred Qualifications

Professional Certification in Data Science and Artificial Intelligence.

Diploma in Education (e.g., Post-secondary Education, Adult Education, and Vocational Education) is preferred.

10+ years of employment experience as a practitioner/professional within the relevant discipline.

Teaching experience in post-secondary, adult training, or industry training environment.

Experience in leadership and innovation in technology-based projects.

Other Required Skills:

A thorough knowledge and work experience in Machine Learning, Deep Learning, Natural Language Processing, Statistical Learning and Modeling, and IoT applications. Candidates with strong expertise in other areas of Data Science and Artificial Intelligence will be considered as well.

Commitment to applied and experiential learning as a pedagogy and a key feature of UDSTu2019s mandate.

Ability to design, develop, deliver, and evaluate authentic learning experiences and assessments. These should incorporate contemporary tools and resources to maximize content learning in context, and to develop the knowledge, skills, competences and attitudes identified in program outcomes.

Digital literacy and demonstrated fluency in technology systems, and an ability to model and facilitate use of current and emerging digital tools to support research and learning.

Demonstrated ability to develop technology-enriched learning environments that enable students to be active participants in their own learning.

Commitment to the effectiveness, vitality, and self-renewal of the teaching profession through self-driven continuous professional development and life-long learning.

Effective oral and written communication skills.

Collaborative and collegial spirit and a demonstrated ability to establish rapport with learners, colleagues, sponsor-employers, and members of the community.

Ability to initiate applied research projects.

How to Apply

Applicants must meet all essential qualifications in order to be shortlisted for the position; other qualifications may be a deciding factor in the selection. Qualifications and experience will be assessed through your application, which may include but not be limited to curricula vitae, mock lectures, motivationletter, references, teaching dossiers and sample publications. It is the applicant’s responsibility to provide appropriate examples that illustrate how s/he meets each requirement. Failing to do so could result in the application being rejected. We thank all applicants for applying for the role; only those selected for further consideration will be contacted.

The First National Applied University offering applied Bachelor’s degrees and Master’s degrees in addition to certificates and diplomas in various .

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