29 Data Science 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

BAE Systems Strategic Aerospace Services WLL | Full time

• Business Area Name: PRIMARY HEALTH CARE CORPORATION (PHCC)
• Job Type: Full time
• Province: Ad Dawhah
• Country: Qatar
• Postal Code: 000

Job Description

• Managing the established directorate learning and development dashboard, metadata presented, quality and integrity of data to ensure timely reports are presented for the management team.
• Working with experts and teams across the organization to ensure quality data is collected, recorded, and reported in a timely and informative way for managers.
• Managing initiatives that support learning and development data quality, including skills development, communications, and guidelines for educators, facilitators, experts, and coordinators.
• Present performance reports, audits, and presentations to management team, with recommendations for quality improvement and efficient knowledge management processes.
• Establish statistical models that provide richer knowledge and insights to performance, gaps, and patterns for workforce development plans and annual learning and development planning cycle.
• Develop data visualization models to support managers in their decision-making and the strategy planning cycle.
• Perform data modeling and reporting for the management team from education and health sectors.
• Analyze large and diverse datasets from across the organization for L&D and those supported externally through external partner stakeholder groups.
• Analyze existing tools and databases and provide software solution recommendations.
• Write comprehensive reports for directorate management team.
• Developing Learning Management System tracking, management, and reporting module, with advanced programming skills to include development of data management processes supported by (but not limited to) programming languages, such as SQL, Oracle, and Python.
• Collecting and interpreting workforce learning and development data from data management tools and systems across PHCC.
• Analyzing results with statistical evidence to support KPIs, L&D performance, and quality.
• Producing data reports and data models for SMT to support decisions, strategy updates, and performance, with data visualization, development of report programs, presentation, maintenance of data integrity processes.
• Identifying patterns and trends in datasets through the use of program models, making recommendations for the management team on quality improvement or efficiency measures required.
• Working alongside teams to establish directorate needs for data management, and developing teams in data management, presentation, and reporting.
• Developing data management and knowledge management skills for team members and those supporting the learning and development cycle.
• Defining enhanced data collection and analysis processes, including management of data management system, directorate dashboard, balanced scorecard, and reporting cycle.
• Benchmarking effective knowledge management models, practice, and tools for health care workforce development.
• Supporting enhanced PHCC Learning Management System development and performance reporting updates for PHCC balanced scorecard.
• Providing technical expertise in data storage structures, data mining, and data cleansing.
• Development of knowledge management standards and models for directorate plans, PHCC Corporate Strategic Plan, delivery, and outcomes.
• Assessment and evaluation of newly introduced initiatives for quality improvement cycle and further development of knowledge – data management processes and models.
• The incumbent will undertake any such appropriate duties or responsibilities as directed.
• Ensure high standards of confidentiality to safeguard any sensitive information.

Requirements

• Bachelor’s degree in information technology, computer science, statistics, and/or mathematics, economics, or information management. Post Graduate Degree is preferred.
• Professional certification to include IT, programming or coding, statistical software, knowledge management, data management and analytics, education management, healthcare management or general management.
• 5 years’ experience in a specialist data analyst role working in the education or health sector.
• Other professional experience being considered for this role as an essential requisite includes:
• Management of health care data or business intelligence experience.
• IT professional certification, programming and statistical software, and data management.
• Developing data management, analysis, and reporting skills for team members.
• Performance reporting for strategy implementation, audit progress, standards compliance and governance, and decision-making processes supporting middle management teams.
• Strong verbal, presentation, and written communication skills.
• An analytical mind for problem-solving, making recommendations for performance and quality improvements.
• Attention to detail; interpreting data for meaningful action plans supporting directorate KPIs, with accuracy and attention to detail.
• Methodical and logical approach to problem solving and recommendations within context of business plan implementation and improvement to knowledge management practice.
• Strong interpersonal skills and teamwork across immediate team and stakeholders across PHCC.
• Risk and change management with impact assessment, including adoption of new innovative solutions to data management and knowledge.
• Bilingual in Arabic and English language (preference as data sets and management will include interpreting data in both languages, as well as business communications).

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