22 Predictive Analytics jobs in Qatar

Job Summary
You will be responsible for end-to-end data science cycles, encompassing designing, training, implementing, evaluating, and monitoring machine learning models, and will also design and implement highly scalable tools and algorithms based on state-of-the-art Machine Learning and Deep Learning methodologies.

You will work across the ML stack, from researching models, working with large datasets, training, and tuning existing models to creating new models, deploying them at scale, analyzing results, and presenting findings to stakeholders across tech and business domains.

Job Objectives

• Develop and implement advanced predictive models to optimize customer experiences and other business outcomes.
• Analyze large and complex datasets to extract actionable insights and drive business decisions.
• Interpret results and provide actionable insights to guide real-time decision-making within the business context.
• Collaborate with cross-functional teams to ensure proper deployment and integration of ML models for new releases.

Job Responsibilities
Predictive Modeling and Deployment

• Develop and implement advanced predictive models to forecast key business metrics such as sales, customer churn, or product demand.
• Utilize predictive modeling to optimize customer experiences and other business outcomes.
• Execute machine learning models, algorithms, and statistical techniques to analyze historical data and ensure scalability and efficiency.

Data Preparation and Analysis

• Develop and use advanced software programs, algorithms, and query techniques to cleanse, integrate, and evaluate datasets for model inputs.
• Analyze large and complex datasets to extract actionable insights and identify trends and patterns that can drive business decisions.
• Identify manual human processes, understand user behaviors, and analyze use cases that can be augmented or automated.

Model Deployment and Interpretation

• Deploy models into production environments and monitor their performance over time.
• Apply statistical, mathematical, and predictive modeling techniques to build, maintain, and improve real-time decision systems.
• Interpret results, develop insights within the business context, and provide guidance on risks and limitations

Development & Documentation

• Write the code as per agreed software design rules to keep it aligned with the rest of the code base.
• Code the final implementation that the generated code is referring to.
• Follow company software data protection and security guidelines in developing software.
• Accurately estimate the time needed to complete an assigned task.
• Identify possible causes of issues or problems.
• Think through and recommend solutions when raising issues around code, requirements, etc.
• Write technical design documentation that fully defines all application code.
• Maintain detailed knowledge of iHorizons products and services.
• Understand the business impact for labs outcomes.

Collaboration & Team Guidance

• Stay updated on the latest research, learn new applications, tools, and technologies in the fields of data science and machine learning through intensive and focused effort.
• Collaborate with technical and non-technical business partners to develop analytical dashboards describing ML algorithm findings to stakeholders.
• Collaborate with other teams to perform code reviews and oversee proper deployment for new releases.
• Actively mentor and support mid-level and junior developers in their professional growth.
• Provide guidance on best practices in machine learning, code reviews, and project design.
• Foster an inclusive and collaborative environment that encourages continuous learning and development within the team.
• Oversee interactions with vendors and third-party service providers, including collaborating on the design and implementation of technical architectures, and acting as a point of contact for resolving technical issues. Maintain clear communication with internal stakeholders regarding vendor-related activities, updates, and issues to facilitate smooth collaboration and decision-making processes.

Job Requirements
Educational Qualification

• Bachelor's degree in data science, statistics, and computer science is a MUST.
• Google Cloud - Professional Machine Learning Engineer Certificate
• Google AgentSpace implementation experience

Previous Work Experience

• 3-4+ Years of experience in data science or machine learning.
• Must have strong experience in at least one of the following areas:
• Vision models
• NLP models (Experience in Arabic NLP is a huge plus)

Skills And Abilities

• Proficient in python, TensorFlow, keras and pytorch.
• Good experience in:
• SQL and non-relational databases.
• Data analytics reports generation.
• ML model development deployment.

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Main tasks and responsibilities (the position exists to perform the below functions and essential activities)

Build and optimize web applications from the front end to the back end.

Integrate user-facing elements using server-side logic and connecting the application with the cloud infrastructure.

Design and implement databases to store and retrieve data efficiently.

Optimize database performance and ensure data integrity.

Develop data pipelines for ETL (Extract, Transform, Load) processes.

Design, develop, and implement machine learning models to solve specific business problems using algorithms suitable for the task.

Identify and select relevant features or variables that contribute to the performance of machine learning models.

Analyse and understand large data sets to identify patterns, trends, and insights relevant to business goals.

Clean and prepare raw data for analysis, ensuring data quality and handling missing and inconsistent information.

Integrate and process data from various sources to support business needs.

Implement security measures for cloud-based solutions, including access controls, encryption, and compliance with industry standards. Monitor and optimize the performance of cloud-based applications and infrastructure.

Identify and address bottlenecks to ensure optimal system performance.

Collaborate with cross-functional teams, including other developers, data scientists, and system administrators.

Communicate technical concepts effectively to non-technical stakeholders.

Adhere to agile development methodologies and participate in sprint planning, reviews, and retrospectives.

Develop and maintain database architectures using MSSQL.

Collaborate with stakeholders to gather and comprehend business requirements for data collection and analysis.

Perform data validation to ensure accuracy, completeness, and consistency of data.

Analyse data sets, generate insights, and create reports using Power BI or similar tools.

Utilize Python for data manipulation, analysis, and automation tasks.

Integrate and work with various APIs for data extraction and manipulation.

Oryx Universal College in partnership with Liverpool John Moores University | Full time

We are seeking a highly skilled and innovative Artificial Intelligence and Machine Learning Engineer to join our team. The ideal candidate will be responsible for designing, developing, and deploying AI and ML models that drive impactful solutions across various domains, including education, data analytics, automation, and smart systems. You will work alongside interdisciplinary teams to integrate cutting-edge technologies into practical applications, transforming data into intelligent action.

Key Responsibilities:

• Design, train, evaluate, and deploy machine learning and deep learning models
  
• Build and maintain scalable AI solutions for real-time or batch processing systems.
  
• Optimise model performance, including accuracy, latency, and resource consumption.
  
• Collaborate with data engineers and analysts to source, clean, and transform data.
  
• Apply advanced statistical and data mining techniques to extract meaningful patterns.
  
• Stay updated with the latest advancements in AI and ML technologies.
  
• Prototype innovative solutions, contribute to research publications, and recommend adoption of new frameworks.
  
• Systems Integration
  
• Develop APIs and services to integrate AI solutions into existing platforms or applications.
  
• Collaborate with software engineers and DevOps teams to ensure production-level stability.
  
• Work closely with academic and operational teams to understand business needs and translate them into technical solutions.
  
• Prepare documentation, reports, and presentation materials to communicate findings and methodologies.
  

Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field (Master’s or PhD preferred).

Minimum 3 years of hands-on experience in AI/ML engineering or data science roles.

Proficient in Python and common ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Keras).

Strong understanding of machine learning algorithms, neural networks, natural language processing (NLP), and computer vision.

Experience in model deployment using cloud platforms (e.g., AWS, Azure, GCP) or containerised environments (Docker, Kubernetes).

Knowledge of MLOps tools and CI/CD pipelines for ML projects.

Familiarity with big data platforms (e.g., Spark, Hadoop).

Experience with academic or educational systems (LMS, AI in education) is a plus.

Demonstrated contributions to open-source projects, research publications, or hackathons.

We are seeking a highly skilled and innovative Artificial Intelligence and Machine Learning Engineer to join our team. The ideal candidate will be responsible for designing, developing, and deploying AI and ML models that drive impactful solutions across various domains, including education, data analytics, automation, and smart systems. You will work alongside interdisciplinary teams to integrate cutting-edge technologies into practical applications, transforming data into intelligent action.

1. Model Development & Deployment
   1. Design, train, evaluate, and deploy machine learning and deep learning models.
   2. Build and maintain scalable AI solutions for real-time or batch processing systems.
   3. Optimize model performance, including accuracy, latency, and resource consumption.
2. Data Engineering & Processing
   1. Collaborate with data engineers and analysts to source, clean, and transform data.
   2. Apply advanced statistical and data mining techniques to extract meaningful patterns.
3. Research & Innovation
   1. Stay updated with the latest advancements in AI and ML technologies.
   2. Prototype innovative solutions, contribute to research publications, and recommend adoption of new frameworks.
4. Systems Integration
   1. Develop APIs and services to integrate AI solutions into existing platforms or applications.
   2. Collaborate with software engineers and DevOps teams to ensure production-level stability.
5. Collaboration & Communication
   1. Work closely with academic and operational teams to understand business needs and translate them into technical solutions.
   2. Prepare documentation, reports, and presentation materials to communicate findings and methodologies.

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field (Master’s or PhD preferred).
• Minimum 3 years of hands-on experience in AI/ML engineering or data science roles.
• Proficient in Python and common ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Keras).
• Strong understanding of machine learning algorithms, neural networks, natural language processing (NLP), and computer vision.
• Experience in model deployment using cloud platforms (e.g., AWS, Azure, GCP) or containerized environments (Docker, Kubernetes).

• Knowledge of MLOps tools and CI/CD pipelines for ML projects.
• Familiarity with big data platforms (e.g., Spark, Hadoop).
• Experience with academic or educational systems (LMS, AI in education) is a plus.
• Demonstrated contributions to open-source projects, research publications, or hackathons.

Scale's rapidly growing International Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of:

• Creating custom AI applications that will impact millions of citizens
• Generating high-quality training data for national LLMs
• Upskilling and advisory services to spread the impact of AI

We are hiring a Machine Learning Engineer Manager who will manage a team of high-calibre MLEs who design, train, deploy, and evaluate computer vision and/or LLMs to power custom applications we build for our public sector clients. You will guide your team towards using data-driven experiments to provide key insights around model strengths and inefficiencies in an effort to improve products.

At Scale, we're not just building AI solutions—we're enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you're ready to shape the future of AI in the public sector and be a founding member of our team, we'd love to hear from you.

You will:

• Train state of the art models, developed both internally and from the community, in production to solve problems for our enterprise customers.
• Manage a team of ML Engineers
• Work with product and research teams to identify opportunities for ongoing and upcoming services.
• Explore approaches that integrate human feedback and assisted evaluation into existing product lines.
• Create state of the art techniques to integrate tool-calling into production-serving LLMs.
• Work closely with customers - some of the most sophisticated ML organizations in the world - to quickly prototype and build new deep learning models targeted at multi-modal content understanding problems.

Ideally you'd have:

• At least 5 years of model training, deployment and maintenance experience in a production environment
• At least 5+ years of management or tech leadership experience
• Strong skills in NLP, LLMs and deep learning
• Solid background in algorithms, data structures, and object-oriented programming
• Experience working with a cloud technology stack (eg. AWS, GCP, or Azure) and developing machine learning models in a cloud environment
• Experience building products with LLMs including knowing the ins and outs of evaluation, experimentation, and designing solutions to get the most of the models
• Strong written and verbal communication skills to operate in a cross functional team environment

Nice to haves:

• Experience in dealing with large scale AI problems, ideally in the generative-AI field
• Demonstrated expertise in large vision-language models for diverse real-world applications, e.g. classification, detection, question-answering, etc.
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, etc.) and/or journals
• Strong high-level programming skills (e.g., Python), frameworks and tools such as DeepSpeed, Pytorch lightning, kubeflow, TensorFlow, etc.
• Fluent in Arabic

PLEASE NOTE:
Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at Please see the United States Department of Labor's
Know Your Rights poster
for additional information.
We comply with the United States Department of Labor's
Pay Transparency provision
.
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We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.