2 545 Data jobs in Bahrain

• Developing and deploying machine learning models for resource estimation, ore grade prediction, and production forecasting.
• Analyzing complex geological and operational data to identify patterns, anomalies, and opportunities for efficiency gains.
• Designing and implementing data pipelines for collecting, cleaning, and processing large volumes of mining-related data from various sources (e.g., sensors, surveys, historical records).
• Collaborating with domain experts to understand their challenges and translate them into data science problems.
• Building interactive dashboards and visualizations to communicate insights to stakeholders across the company.
• Evaluating and recommending new data science tools and technologies relevant to the mining industry.
• Staying current with the latest advancements in data science, machine learning, and AI, particularly in earth sciences and resource management.
• Contributing to a culture of data-driven decision-making throughout the organization.
• Mentoring junior data scientists and sharing knowledge within the team.

• Develop, implement, and validate advanced statistical and machine learning models to analyze mining data.
• Extract, clean, and preprocess large datasets from various sources, including sensors, geological reports, and operational logs.
• Identify key performance indicators (KPIs) and develop dashboards and reports to track operational efficiency and predict potential issues.
• Design and build predictive models for equipment failure, production output, and resource grade.
• Apply data science techniques to optimize mine planning, scheduling, and resource allocation.
• Collaborate with geologists, engineers, and operations managers to understand data challenges and deliver actionable insights.
• Research and implement new data science methodologies and technologies relevant to the mining sector.
• Communicate complex findings and recommendations clearly to technical and non-technical stakeholders.
• Contribute to the development of a data-driven culture within the organization.
• Ensure data quality, integrity, and security throughout the analytical process.
• Mentor junior data scientists and contribute to the growth of the data science team.

• Ph.D. or Master's degree in Data Science, Statistics, Computer Science, Mining Engineering, or a related quantitative field.
• Minimum of 6 years of professional experience as a Data Scientist, with a strong emphasis on applying data science in the mining or natural resources sector.
• Proven expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, time series analysis, deep learning), and their practical application.
• Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas, NumPy).
• Experience with big data technologies (e.g., Spark, Hadoop) and database management (SQL, NoSQL).
• Familiarity with geological data, geostatistics, and mine planning software is highly desirable.
• Strong understanding of operational challenges and optimization in the mining industry.
• Excellent problem-solving, analytical, and critical thinking skills.
• Exceptional communication and presentation skills, with the ability to translate complex data insights into business strategies.
• Experience with data visualization tools (e.g., Tableau, Power BI).
• Ability to work independently and collaboratively in a fully remote environment.

• Lead the design, development, and deployment of sophisticated data science models and machine learning algorithms tailored for the mining industry.
• Utilize large datasets from exploration, extraction, processing, and operational monitoring to derive actionable insights and predictive capabilities.
• Develop and implement strategies for data collection, cleaning, feature engineering, and model validation specific to mining-related data.
• Collaborate closely with geologists, mining engineers, operational managers, and other stakeholders to identify key business challenges and translate them into data science problems.
• Build and maintain robust data pipelines and analytical frameworks for real-time monitoring and decision support.
• Mentor and guide a team of data scientists and analysts, fostering a culture of innovation and technical excellence in a remote setting.
• Evaluate and implement new data science tools, technologies, and methodologies relevant to the mining sector.
• Communicate complex analytical findings and recommendations clearly and effectively to both technical and non-technical audiences through reports, presentations, and visualizations.
• Ensure the ethical and responsible use of data and AI in mining operations.
• Stay abreast of the latest advancements in data science, machine learning, and their applications within the resources and mining industry.

• Lead the development and implementation of data-driven solutions to address key challenges in mining operations, including predictive maintenance, resource estimation, and process optimization.
• Design, build, and deploy sophisticated machine learning models using large, complex datasets from geological surveys, sensor data, and operational logs.
• Analyze vast amounts of data to identify trends, patterns, and anomalies that can lead to improved operational efficiency, cost reduction, and enhanced safety protocols.
• Develop and maintain robust data pipelines and workflows for data ingestion, cleaning, transformation, and analysis.
• Collaborate closely with geologists, engineers, and operational managers to understand their needs and translate them into data science initiatives.
• Communicate complex analytical findings and recommendations clearly and concisely to both technical and non-technical stakeholders through reports, presentations, and visualizations.
• Stay at the forefront of data science and machine learning advancements, evaluating and implementing new tools and methodologies.
• Mentor and guide junior data scientists, fostering a culture of innovation and continuous learning within the team.
• Ensure the ethical and responsible use of data, adhering to all relevant data privacy regulations.
• Develop dashboards and reporting tools to monitor key performance indicators (KPIs) related to mining operations.
• Contribute to the strategic direction of data analytics within the organization.

• Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• Minimum of 7 years of progressive experience as a Data Scientist, with at least 3 years in a lead or senior capacity.
• Proven expertise in developing and deploying machine learning models (e.g., regression, classification, clustering, deep learning) using Python or R.
• Strong proficiency in SQL and experience with big data technologies (e.g., Spark, Hadoop).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices.
• Familiarity with statistical modeling, experimental design, and data visualization techniques.
• Excellent problem-solving skills and the ability to think critically and creatively.
• Strong communication and presentation skills, with the ability to explain technical concepts to diverse audiences.
• Experience in the mining or natural resources sector is highly advantageous.
• Ability to work independently and manage projects effectively in a fully remote setting.
• Fluency in English is required.

• Develop and implement advanced statistical and machine learning models for mining operations.
• Analyze large datasets from various sources to identify trends and patterns.
• Design and execute data mining strategies to optimize resource exploration and extraction.
• Build predictive models for equipment failure, safety incidents, and production forecasts.
• Collaborate with domain experts to define analytical problems and develop solutions.
• Communicate complex analytical findings and recommendations to stakeholders.
• Develop data visualization tools and dashboards for operational insights.
• Stay updated with the latest advancements in data science and machine learning techniques.
• Contribute to the development of data strategies and best practices.
• Mentor junior data scientists and promote data-driven decision-making.

• Ph.D. or Master's degree in Data Science, Computer Science, Statistics, or a related quantitative field.
• 7+ years of experience in data science, with a focus on applying ML/AI in industrial settings.
• Expertise in Python or R, including relevant data science libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of database technologies and SQL.
• Proven experience in statistical modeling, machine learning, and data mining.
• Excellent problem-solving and analytical skills.
• Exceptional communication and presentation skills, with the ability to explain technical concepts to diverse audiences.
• Experience working with large, complex datasets.
• Ability to work independently and manage projects effectively in a remote setting.

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

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