33 Data Mining jobs in Bahrain

• Define the personalization and recommendation strategy aligned with business goals and client experience vision.
• Lead, mentor, and grow a team of data scientists and machine learning engineers.
• Collaborate cross-functionally with product, marketing, engineering, and commercial teams to embed data-driven personalization across all client touchpoints.
  
  

• Design, build, and deploy ML/AI models for:
• Personalized investment recommendations
• Smart content curation
• Behavioral and predictive analytics
• Funnel optimization and conversion predictions
• Drive experimentation and continuous model performance improvement using A/B testing and data validation techniques.
• Ensure model explainability, fairness, and compliance with relevant data privacy regulations.
  

• Architect and oversee the personalization engine powering mobile, web, and CRM systems.
• Implement real-time data processing pipelines for adaptive personalization.
• Collaborate with data engineering to ensure scalable, high-quality data infrastructure and feature pipelines.
  
  

• Translate data into actionable insights to inform client segmentation, lifecycle management, and journey personalization.
• Develop dashboards and KPIs to measure impact of personalization initiatives on user engagement and business outcomes.
  
  

• Strong product sense with a deep understanding of client behavior in digital financial services.
• A passion for using data to improve lives and decision-making for HNW individuals.
• Strategic and hands-on: able to drive vision and execute technical implementation.
• Collaborative leadership and stakeholder communication skills.
• Highly analytical with strong attention to detail and data integrity.
  
  

• Master’s or PhD in Data Science, Machine Learning, Computer Science, or related field.
• 6+ years of experience in applied data science, with 2+ years in a leadership or managerial role.
• Proven experience developing personalization and recommendation systems at scale.
• Proficiency in Python, SQL, and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with data platforms such as Databricks, AWS/GCP/Azure, and real-time data systems (e.g., Kafka).
• Background in fintech, wealth management, or e-commerce personalization is a strong plus
  
  

The Family Office is an independent wealth management firm offering customized investment solutions in alternative asset classes, including private equity, private debt, and real estate. Serving high-net-worth individuals and families, we provide tailored strategies to address unique financial needs with a focus on transparency, diversification, and long-term value. With a commitment to excellence and decades of expertise, The Family Office helps clients preserve and grow their wealth across generations.

We are seeking a Data Science Manager & Head of Recommendations and Personalization to lead the development of intelligent, data-driven client experiences across our digital platforms. You will spearhead the design and implementation of machine learning models for personalized investment recommendations, content targeting, and client engagement optimization.

This is a high-impact role for a strategic data leader who thrives in a fast-paced environment and has experience building and scaling personalization systems—ideally in fintech, digital wealth, or consumer platforms.

• Define the personalization and recommendation strategy aligned with business goals and client experience vision.
• Lead, mentor, and grow a team of data scientists and machine learning engineers.
• Collaborate cross-functionally with product, marketing, engineering, and commercial teams to embed data-driven personalization across all client touchpoints.

• Design, build, and deploy ML/AI models for:
  • Personalized investment recommendations
  • Smart content curation
  • Behavioral and predictive analytics
  • Funnel optimization and conversion predictions
• Drive experimentation and continuous model performance improvement using A/B testing and data validation techniques.
• Ensure model explainability, fairness, and compliance with relevant data privacy regulations.

• Architect and oversee the personalization engine powering mobile, web, and CRM systems.
• Implement real-time data processing pipelines for adaptive personalization.
• Collaborate with data engineering to ensure scalable, high-quality data infrastructure and feature pipelines.

• Translate data into actionable insights to inform client segmentation, lifecycle management, and journey personalization.
• Develop dashboards and KPIs to measure impact of personalization initiatives on user engagement and business outcomes.

• Strong product sense with a deep understanding of client behavior in digital financial services.
• A passion for using data to improve lives and decision-making for HNW individuals.
• Strategic and hands-on: able to drive vision and execute technical implementation.
• Collaborative leadership and stakeholder communication skills.
• Highly analytical with strong attention to detail and data integrity.

• Master’s or PhD in Data Science, Machine Learning, Computer Science, or related field.
• 6+ years of experience in applied data science, with 2+ years in a leadership or managerial role.
• Proven experience developing personalization and recommendation systems at scale.
• Proficiency in Python, SQL, and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
• Experience with data platforms such as Databricks, AWS/GCP/Azure, and real-time data systems (e.g., Kafka).
• Background in fintech, wealth management, or e-commerce personalization is a strong plus

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.

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.

• 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.

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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
  
  
  

• Master's degree or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related field
• A minimum of 7+ years of experience in data science or analytics, with 3+ years in a leadership role managing data science teams
• Proficient in programming languages such as Python, R, and experience with big data technologies (e.g., Hadoop, Spark)
• Deep understanding of machine learning techniques, statistical modeling, and advanced analytics methodologies
• Proven track record of successfully leading and delivering large-scale data science projects that drive business value
• Expertise in data visualization tools (e.g., Tableau, Power BI) for effectively communicating complex analyses
• Strong project management skills and ability to lead teams in a fast-paced environment
• Excellent analytical and strategic thinking skills, with a focus on results
• Outstanding communication and interpersonal skills, with the ability to convey technical information to non-technical stakeholders in English and Arabic
  
  

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

• Seniority level Mid-Senior level

• Employment type Full-time

• Job function Information Technology
• Industries IT Services and IT Consulting

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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
  
  
  

• Master's degree or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related field
• A minimum of 7+ years of experience in data science or analytics, with 3+ years in a leadership role managing data science teams
• Proficient in programming languages such as Python, R, and experience with big data technologies (e.g., Hadoop, Spark)
• Deep understanding of machine learning techniques, statistical modeling, and advanced analytics methodologies
• Proven track record of successfully leading and delivering large-scale data science projects that drive business value
• Expertise in data visualization tools (e.g., Tableau, Power BI) for effectively communicating complex analyses
• Strong project management skills and ability to lead teams in a fast-paced environment
• Excellent analytical and strategic thinking skills, with a focus on results
• Outstanding communication and interpersonal skills, with the ability to convey technical information to non-technical stakeholders in English and Arabic
  
  

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

• Design, develop, and implement machine learning algorithms and models, from conception to production.
• Build and optimize robust data pipelines for data ingestion, transformation, and feature extraction.
• Collaborate with data scientists and research engineers to transition prototypes into production-ready solutions.
• Evaluate model performance, conduct A/B testing, and continuously improve model accuracy and efficiency.
• Deploy and manage machine learning models in cloud environments (e.g., AWS, Azure, GCP).
• Implement MLOps best practices for model versioning, monitoring, and retraining.
• Write clean, efficient, and well-documented code in Python or other relevant languages.
• Stay updated with the latest advancements in machine learning, deep learning, and artificial intelligence.
• Troubleshoot and debug production ML systems.
• Participate in code reviews and contribute to the overall technical architecture.
• Communicate complex technical concepts to non-technical stakeholders.

• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related quantitative field.
• Proven experience (4+ years) as a Machine Learning Engineer or similar role.
• Strong proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Pandas, NumPy).
• Experience with building and deploying ML models in production environments.
• Solid understanding of machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning, deep learning).
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Familiarity with MLOps tools and practices.
• Strong problem-solving skills and ability to work with large, complex datasets.
• Excellent communication and collaboration skills, able to work effectively in a remote team setting.
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.

• Design, develop, and implement robust machine learning models and algorithms to address specific business challenges and enhance existing products/services.
• Collect, preprocess, clean, and analyze large, complex datasets, preparing them effectively for model training and evaluation.
• Train, test, and validate machine learning models rigorously, ensuring high accuracy, robust performance, and generalization capabilities.
• Deploy machine learning models into production environments and seamlessly integrate them with existing software systems and platforms.
• Optimize models for performance, scalability, efficiency, and resource utilization, including memory and computation.
• Perform extensive feature engineering and selection to improve model effectiveness and predictive power.
• Conduct experiments, A/B tests, and research to explore new machine learning techniques, emerging technologies, and cutting-edge algorithms.
• Collaborate closely with data scientists, software engineers, and product managers to define project requirements, translate them into technical specifications, and deliver end-to-end solutions.
• Monitor and maintain deployed ML models, retraining, updating, and fine-tuning them as necessary to ensure continued relevance and performance.
• Document model architecture, development processes, code, and performance metrics comprehensively.
• Participate actively in code reviews, providing constructive feedback and ensuring adherence to best practices in software development and ML engineering.
• Stay consistently updated with the latest advancements in AI, machine learning, deep learning research, and relevant industry trends.
• Develop robust and efficient data pipelines for both training and inference data flows.
• Troubleshoot and debug complex issues related to ML models, data pipelines, and deployment environments.
• Communicate complex technical concepts and model insights clearly and effectively to non-technical stakeholders.
• Contribute to the research and potential publication of innovative solutions and methodologies.
• Ensure data privacy, security, and ethical AI compliance in all machine learning initiatives.
• Implement MLOps practices for efficient model lifecycle management, versioning, and continuous integration/delivery.
• Evaluate and select appropriate ML frameworks, libraries, and tools based on project requirements and best practices.
• Mentor junior team members, share knowledge, and contribute to the growth of the engineering team.

• Master's or Ph.D. degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field.
• Minimum of 3-5 years of practical experience as a Machine Learning Engineer or Data Scientist in a professional setting.
• Strong proficiency in programming languages such as Python (with extensive experience in libraries like TensorFlow, PyTorch, Scikit-learn, Keras).
• Solid understanding of core machine learning algorithms (e.g., supervised, unsupervised, reinforcement learning) and deep learning architectures (CNNs, RNNs, Transformers).
• Extensive experience with data processing and manipulation tools (e.g., Pandas, NumPy, Spark).
• Proficiency with cloud platforms (AWS, Azure, GCP) and familiarity with MLOps tools (e.g., MLflow, Kubeflow, Sagemaker) is highly desirable.
• Experience with big data technologies (e.g., Spark, Hadoop, Kafka) is a plus.
• Strong mathematical and statistical background, including linear algebra, calculus, and probability.
• Excellent problem-solving skills and ability to work with large, complex, and sometimes messy datasets.
• Strong communication and collaboration skills, able to articulate technical solutions clearly.
• Ability to work effectively both independently and as part of a cross-functional team in a hybrid environment.
• Experience with version control systems (e.g., Git) and agile development methodologies.
• A portfolio of past ML projects, contributions to open-source initiatives, or relevant publications is a strong advantage.
• Research-oriented mindset with a passion for innovation and pushing the boundaries of AI.

• Design, develop, and implement machine learning models and algorithms for various applications.
• Work with large datasets to preprocess, analyze, and extract features for model training.
• Train, evaluate, and optimize machine learning models for performance and efficiency.
• Deploy machine learning models into production environments and monitor their performance.
• Collaborate with data scientists, software engineers, and product managers to integrate AI solutions into products.
• Research and stay updated on the latest advancements in machine learning, deep learning, and AI research.
• Develop and maintain robust MLOps pipelines for continuous integration and deployment of models.
• Perform A/B testing and statistical analysis to validate model effectiveness.
• Contribute to technical documentation, research papers, and presentations.
• Troubleshoot and debug issues related to machine learning models and infrastructure.

• Master’s or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
• Minimum of 3-5 years of hands-on experience in machine learning engineering.
• Strong proficiency in programming languages such as Python, with expertise in ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with data processing and big data technologies (e.g., SQL, Spark, Hadoop).
• Solid understanding of machine learning algorithms, statistical modeling, and deep learning architectures.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes) for ML deployment.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills, with the ability to explain complex technical concepts.
• Experience with MLOps practices and tools is highly desirable.
• A portfolio of relevant projects or published research is a plus.