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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
  
  
  

• 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
  
  

• 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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Manama, Capital Governorate, Bahrain 3 weeks ago

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• 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

• Assisting in the collection, cleaning, and preprocessing of large datasets.
• Performing statistical analysis and applying machine learning algorithms under supervision.
• Developing data visualizations to communicate insights and findings.
• Contributing to the development and testing of predictive models.
• Collaborating with cross-functional teams to understand data needs and deliver solutions.
• Learning and applying new data science tools and methodologies.
• Documenting processes, methodologies, and results.
• Participating in team meetings and presenting findings.
• Developing a strong understanding of business problems and how data can solve them.
• Proactively identifying opportunities to improve data processes and analyses.

• Assisting in data cleaning, preprocessing, and feature engineering.
• Developing and implementing statistical models and machine learning algorithms.
• Conducting exploratory data analysis to identify trends and patterns.
• Creating compelling data visualizations to communicate findings.
• Participating in team meetings and contributing to project discussions.
• Learning and applying advanced data analysis techniques and tools.
• Collaborating with mentors to define project objectives and deliverables.
• Developing a portfolio of data science projects.

• Assisting in the collection, cleaning, and pre-processing of large datasets.
• Performing exploratory data analysis to identify trends and patterns.
• Developing and implementing machine learning models under supervision.
• Visualizing data and presenting findings to team members.
• Learning and applying various data science tools and programming languages (e.g., Python, R, SQL).
• Collaborating with cross-functional teams to understand data requirements.
• Contributing to the development of data-driven reports and dashboards.
• Participating in team meetings and knowledge-sharing sessions.
• Researching new data science techniques and methodologies.
• Assisting in the documentation of data processes and model development.

• Overseeing the design and execution of the graduate data science program, ensuring alignment with company objectives and industry best practices.
• Providing mentorship and technical guidance to graduate data scientists on their projects and career development.
• Developing and delivering training modules on advanced data science techniques, machine learning algorithms, and statistical modeling.
• Facilitating project-based learning experiences, helping graduates apply their skills to real-world business challenges.
• Evaluating the performance and progress of graduate participants, providing constructive feedback.
• Collaborating with hiring managers and HR to identify potential hires from the graduate pool and facilitate their integration into full-time roles.
• Keeping the program curriculum updated with the latest advancements in data science, AI, and machine learning.
• Organizing knowledge-sharing sessions, workshops, and networking events for the graduate cohort.
• Contributing to the company's data science initiatives by advising on research directions and technical challenges.
• Ensuring a positive and productive learning environment for all participants.

• Advanced degree (Master's or Ph.D.) in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 5 years of professional experience in data science, machine learning, or AI, with a strong track record of success.
• Proven experience in mentoring, coaching, or managing junior data scientists or interns.
• Deep expertise in statistical analysis, predictive modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and data visualization.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas).
• Familiarity with big data technologies and platforms (e.g., Spark, Hadoop).
• Excellent communication, presentation, and interpersonal skills, with the ability to explain complex technical concepts to a diverse audience.
• Strong project management and organizational skills.
• A passion for education, talent development, and fostering innovation.
• Understanding of the graduate recruitment and development lifecycle is a plus.

• Design, develop, and implement machine learning algorithms and models.
• Process, clean, and transform large datasets for machine learning tasks.
• Build and maintain data pipelines for model training and evaluation.
• Collaborate with data scientists and software engineers to deploy ML models into production.
• Monitor and optimize the performance of deployed models.
• Conduct experiments to test and validate different ML approaches.
• Stay current with the latest advancements in machine learning and AI.
• Document models, algorithms, and processes clearly and concisely.

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
• Proven experience (2+ years) as a Machine Learning Engineer or in a similar role.
• Strong programming skills in Python and experience with ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
• Proficiency in data manipulation and analysis using libraries like Pandas and NumPy.
• Experience with SQL and NoSQL databases.
• Familiarity with cloud platforms (AWS, Azure, GCP) and ML deployment tools.
• Solid understanding of machine learning concepts, algorithms, and best practices.
• Excellent problem-solving abilities and attention to detail.