826 Data Science Intern jobs in Bahrain

Job Summary

We are seeking the 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

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

Job Summary
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.

Key Responsibilities:
Strategy & Leadership

• 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.

Data Science & Modeling

• 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.

Personalization Infrastructure

• 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.

Client-Centric Data Insights

• 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.

Key Attributes & Competencies

• 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.

Qualifications

• 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.

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

• Assist in collecting, cleaning, and preparing data for analysis and modeling.
• Support the development and implementation of machine learning models under guidance.
• Perform exploratory data analysis to identify trends and patterns.
• Help in the creation of reports, dashboards, and visualizations to communicate findings.
• Learn and apply various data science tools and techniques.
• Participate in team meetings and contribute to project discussions.
• Document methodologies and code effectively.
• Assist in testing and validating model performance.
• Understand and adhere to data governance and privacy policies.
• Shadow senior data scientists to gain exposure to diverse projects.
• Contribute to a positive and collaborative team environment.

• Recent graduate with a degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field, or equivalent practical experience.
• Basic understanding of programming concepts, preferably in Python or R.
• Familiarity with basic statistical concepts.
• Eagerness to learn and a strong interest in data science and machine learning.
• Good analytical and problem-solving skills.
• Ability to work both independently and as part of a team.
• Excellent communication skills, both written and verbal.
• Proactive attitude and a desire to take initiative.
• Openness to feedback and a commitment to continuous learning.

• Assisting in the collection, cleaning, and pre-processing of large datasets.
• Learning and applying various statistical and machine learning techniques to analyze data.
• Developing data visualizations to communicate findings effectively.
• Supporting senior data scientists in building and validating predictive models.
• Collaborating with cross-functional teams to understand data needs and project objectives.
• Participating in team meetings, brainstorming sessions, and training workshops.
• Gaining exposure to different data science tools and technologies (e.g., Python, R, SQL, visualization libraries).
• Contributing to documentation and knowledge sharing within the data science team.
• Developing problem-solving skills and analytical thinking.
• Understanding the ethical implications of data usage and AI.

• Work on diverse data science projects across different business units.
• Develop proficiency in data analysis, machine learning algorithms, and data visualization techniques.
• Learn to use industry-standard tools and programming languages such as Python, R, SQL, and data visualization libraries.
• Collaborate with senior data scientists and cross-functional teams.
• Gain hands-on experience in data wrangling, feature engineering, model building, and performance evaluation.
• Receive mentorship and guidance from experienced professionals in the field.
• Participate in workshops, training sessions, and knowledge-sharing forums.
• Contribute to actionable insights that drive business decisions.
• Develop strong problem-solving and critical thinking skills.
• Build a professional network within a leading organization.

• Assist in collecting, cleaning, and organizing large datasets.
• Support the development and implementation of machine learning models.
• Perform statistical analysis and data interpretation.
• Create data visualizations to present findings effectively.
• Collaborate with senior data scientists on ongoing projects.
• Learn and apply data mining techniques.
• Assist in documenting data processes and model performance.
• Participate in team meetings and contribute ideas.
• Gain practical experience with data science tools and platforms.
• Support A/B testing and experimental design.
• Adhere to data privacy and security protocols.

• High school diploma or equivalent; a degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering) is a strong plus.
• Basic understanding of statistics and probability.
• Familiarity with programming languages like Python or R is beneficial.
• Strong analytical and problem-solving skills.
• Excellent attention to detail.
• Eagerness to learn and a passion for data science.
• Good communication and teamwork abilities.
• Ability to work independently and take initiative.
• Enthusiasm for technology and data-driven insights.
• A proactive attitude towards learning new tools and techniques.