61 Data Modeling jobs in Bahrain
Senior Data Scientist - Financial Modeling
987 Zallaq, Southern
BHD160000 Annually
WhatJobs
Posted 12 days ago
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Job Description
Our client is seeking a highly skilled Senior Data Scientist with a specialization in Financial Modeling to join their thriving team in Zallaq, Southern, BH . This role is integral to developing sophisticated predictive models and analytical frameworks that drive strategic financial decision-making. You will be responsible for the end-to-end lifecycle of data science projects, from data extraction and cleaning to model development, validation, and deployment. Key responsibilities include building and refining complex financial models, performing advanced statistical analysis, and identifying key performance indicators and drivers of financial performance. You will collaborate closely with finance, risk management, and business development teams to understand their analytical needs and translate them into actionable insights. The ideal candidate will possess a strong quantitative background, deep expertise in statistical modeling, machine learning techniques, and programming languages such as Python or R. Experience with financial data sources and a solid understanding of financial markets and instruments are essential. You will also be involved in developing dashboards and visualizations to communicate complex findings to a non-technical audience. This role requires exceptional problem-solving skills, a rigorous approach to analysis, and the ability to work independently as well as part of a team. A Master's or Ph.D. in Data Science, Statistics, Economics, Finance, or a related quantitative field is required, along with several years of relevant professional experience in financial data science. Familiarity with big data technologies and database management is also a plus. This is an outstanding opportunity to leverage your analytical prowess to make a significant impact on the financial strategy of a dynamic organization. You will work with large datasets and cutting-edge analytical tools in a challenging and rewarding environment. While the role is based in our Zallaq, Southern, BH office, offering in-person collaboration and access to our on-site resources, we offer a structured environment that prioritizes a healthy work-life balance. We believe in fostering a culture of continuous learning and professional development, providing opportunities to enhance your skills and advance your career within the company. Join us and be part of a team dedicated to driving financial excellence through data-driven insights.
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0
Junior Data Scientist - Predictive Modeling
45678 Bilad Al Qadeem, Capital
BHD60000 Annually
WhatJobs
Posted 22 days ago
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Job Description
Our client is seeking enthusiastic and bright Junior Data Scientists to join their innovative team. This is a fully remote internship opportunity, providing invaluable hands-on experience in the field of data science and predictive modeling. You will work closely with senior data scientists and analysts, contributing to various projects that leverage data to drive business insights and solutions. The ideal candidate will have a strong foundational knowledge of statistics, programming, and machine learning concepts, coupled with a passion for solving complex problems using data.
Responsibilities:
Qualifications:
This remote internship is a fantastic launchpad for a career in data science. Our operations are centered around Tubli, Capital, BH , but this role is entirely remote.
Responsibilities:
- Assist in the collection, cleaning, and preprocessing of large datasets from various sources.
- Develop, test, and validate predictive models under the guidance of senior team members.
- Perform exploratory data analysis to identify trends, patterns, and insights.
- Contribute to the development of data visualizations to communicate findings effectively.
- Learn and apply various machine learning algorithms and techniques.
- Support the deployment and monitoring of predictive models.
- Collaborate with team members to understand project requirements and objectives.
- Document methodologies, code, and findings clearly and concisely.
- Participate in team meetings and contribute to discussions on data-driven strategies.
- Gain practical experience with industry-standard data science tools and platforms.
Qualifications:
- Currently pursuing a Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
- Foundational understanding of statistical concepts and methods.
- Proficiency in at least one programming language commonly used in data science, such as Python or R.
- Familiarity with data manipulation libraries (e.g., Pandas, NumPy) and machine learning libraries (e.g., Scikit-learn).
- Basic knowledge of SQL for database querying.
- Strong analytical and problem-solving skills.
- Eagerness to learn and adapt to new technologies and methodologies.
- Excellent communication and interpersonal skills.
- Ability to work independently and manage time effectively in a remote environment.
- A genuine interest in artificial intelligence and its applications.
This remote internship is a fantastic launchpad for a career in data science. Our operations are centered around Tubli, Capital, BH , but this role is entirely remote.
This advertiser has chosen not to accept applicants from your region.
1
Senior Insurance Data Scientist - Risk Modeling
901 Southern, Southern
BHD160000 Annually
WhatJobs
Posted 8 days ago
Job Viewed
Job Description
Our client, a leading global insurer, is seeking a highly skilled Senior Insurance Data Scientist to join their innovative risk modeling team. This is a fully remote position, offering the flexibility to work from anywhere while contributing to critical actuarial and risk management functions. You will be instrumental in developing and implementing advanced statistical models and machine learning algorithms to assess and predict insurance risk. This includes pricing complex insurance products, forecasting loss reserves, detecting fraud, and optimizing underwriting processes. The ideal candidate will possess a strong quantitative background, extensive experience with large datasets, and a deep understanding of insurance principles. You will collaborate with actuaries, underwriters, and business stakeholders to translate complex data into actionable insights that drive strategic decision-making. Responsibilities include data exploration, feature engineering, model development, validation, and deployment. You will be expected to stay abreast of the latest advancements in data science, machine learning, and actuarial science, and apply them to solve challenging problems in the insurance domain. A proven ability to communicate technical findings clearly and concisely to both technical and non-technical audiences is essential. The role requires a proactive and analytical mindset, with a strong commitment to producing high-quality, reliable, and robust models. You will work independently, manage your workload efficiently, and contribute to a collaborative, high-performing remote team environment. This role offers significant opportunities for professional growth and the chance to influence the company's risk management strategies on a global scale.
Responsibilities:
Qualifications:
Responsibilities:
- Develop, validate, and deploy advanced statistical and machine learning models for risk assessment and prediction in insurance.
- Analyze large, complex datasets to identify patterns, trends, and correlations relevant to insurance risk.
- Collaborate with actuarial and underwriting teams to refine pricing strategies and reserve calculations.
- Implement data mining techniques for fraud detection and prevention.
- Perform rigorous model testing and validation to ensure accuracy and reliability.
- Communicate complex technical findings and recommendations to business stakeholders effectively.
- Stay current with industry best practices and emerging technologies in data science and actuarial science.
- Contribute to the development and maintenance of data infrastructure and pipelines.
- Mentor junior data scientists and analysts.
- Document methodologies, models, and results thoroughly.
Qualifications:
- Ph.D. or Master's degree in Statistics, Mathematics, Computer Science, Actuarial Science, or a related quantitative field.
- Minimum of 5 years of experience in data science, with a significant focus on the insurance or financial services industry.
- Proven experience in building and deploying predictive models for risk, pricing, or fraud detection.
- Proficiency in programming languages such as Python or R, and relevant libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
- Experience with SQL and big data technologies (e.g., Spark, Hadoop).
- Strong understanding of statistical modeling, machine learning techniques, and experimental design.
- Knowledge of actuarial principles and insurance product lines is highly desirable.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and presentation skills.
- Ability to work independently and manage multiple projects in a remote setting.
This advertiser has chosen not to accept applicants from your region.
2
Remote Principal Data Scientist - Financial Modeling
707 Al Muharraq, Muharraq
BHD180000 Annually
WhatJobs
Posted 10 days ago
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Job Description
Our client, a prestigious global financial institution, is seeking a highly skilled and experienced Remote Principal Data Scientist to lead advanced financial modeling and quantitative analysis efforts. This is a fully remote role, offering the opportunity to work with cutting-edge technology and drive strategic decision-making. You will be responsible for developing, validating, and deploying sophisticated statistical models to address complex financial challenges, including risk assessment, fraud detection, algorithmic trading, and portfolio optimization. This involves leveraging large datasets, employing advanced machine learning techniques, and ensuring the interpretability and accuracy of model outputs. You will play a key role in defining the data science roadmap, mentoring junior data scientists, and collaborating closely with business stakeholders, traders, and risk managers to translate business needs into actionable data-driven insights. The ideal candidate will possess a Ph.D. or Master's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Physics) and have extensive experience in applying data science and machine learning to financial markets. Expertise in programming languages like Python or R, proficiency with data manipulation libraries (e.g., Pandas, NumPy), and experience with deep learning frameworks (e.g., TensorFlow, PyTorch) are essential. Strong communication skills are required to present complex findings clearly and concisely to both technical and non-technical audiences. We are looking for an innovative thinker with a deep understanding of financial instruments and markets, capable of driving significant impact through advanced analytics. This role offers a challenging and rewarding opportunity to shape the future of quantitative finance.
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3
Remote Lead Data Scientist (Financial Modeling)
90210 Hamad Town, Northern
BHD150000 Annually
WhatJobs
Posted 16 days ago
Job Viewed
Job Description
Our client, a prestigious global investment bank, is looking for an exceptional Remote Lead Data Scientist to spearhead their advanced financial modeling initiatives. This is a fully remote opportunity to work with a world-class team, leveraging vast datasets to build predictive models that drive strategic financial decisions. You will be instrumental in developing and deploying sophisticated machine learning models for risk assessment, fraud detection, algorithmic trading, and portfolio optimization. The ideal candidate possesses a profound understanding of statistical modeling, machine learning algorithms, and financial markets.
Responsibilities:
Responsibilities:
- Lead the design, development, and implementation of advanced statistical and machine learning models for financial applications.
- Analyze large, complex financial datasets to identify trends, patterns, and actionable insights.
- Develop predictive models for risk management, credit scoring, fraud detection, market forecasting, and algorithmic trading strategies.
- Collaborate with quantitative analysts, traders, and portfolio managers to understand business needs and translate them into data science solutions.
- Mentor and guide a team of data scientists, fostering a culture of innovation and technical excellence.
- Evaluate and select appropriate algorithms and tools for specific modeling tasks.
- Ensure the robustness, scalability, and accuracy of deployed models.
- Communicate complex analytical findings and model insights to both technical and non-technical audiences.
- Stay abreast of the latest research and advancements in data science, machine learning, and financial technology.
- Contribute to the development of data infrastructure and best practices within the data science team.
- Ph.D. or Master's degree in Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.
- Extensive experience (7+ years) as a Data Scientist, with a significant focus on financial modeling and quantitative finance.
- Proven leadership experience managing and mentoring data science teams.
- Deep expertise in machine learning techniques (e.g., regression, classification, time series analysis, deep learning) and statistical modeling.
- Proficiency in programming languages such as Python (with libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL.
- Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
- Strong understanding of financial markets, instruments, and regulatory environments.
- Excellent problem-solving skills and the ability to work independently in a remote, fast-paced environment.
- Superb communication and presentation skills, with the ability to explain complex models to diverse stakeholders.
- Experience with financial data providers (e.g., Bloomberg, Refinitiv) is a plus.
This advertiser has chosen not to accept applicants from your region.
4
Principal Insurance Data Scientist - Risk Modeling
222 Hamad Town, Northern
BHD130000 Annually
WhatJobs
Posted 17 days ago
Job Viewed
Job Description
Our client, a highly respected and innovative insurance provider, is seeking a Principal Insurance Data Scientist to spearhead their advanced risk modeling initiatives. This is a fully remote position, offering you the opportunity to leverage your expertise in data science and actuarial principles to drive strategic decision-making from anywhere. You will be instrumental in developing sophisticated predictive models for risk assessment, pricing, fraud detection, and claims analysis. The ideal candidate possesses a deep understanding of insurance operations, advanced statistical modeling techniques, and proficiency in programming languages commonly used in data science.
Responsibilities:
Qualifications:
Responsibilities:
- Design, develop, and implement advanced statistical and machine learning models for insurance risk assessment, pricing, and forecasting.
- Analyze large datasets to identify trends, patterns, and insights related to insurance policies, claims, and customer behavior.
- Develop predictive models for fraud detection and prevention.
- Collaborate with actuarial teams to refine pricing strategies and ensure regulatory compliance.
- Build and maintain data pipelines and analytical frameworks to support ongoing modeling efforts.
- Evaluate the performance of existing models and implement improvements as needed.
- Stay current with the latest advancements in data science, machine learning, and actuarial science.
- Communicate complex analytical findings and recommendations to stakeholders, including senior management and non-technical teams.
- Mentor junior data scientists and contribute to the development of the data science team.
- Ensure the ethical and responsible use of data in all analytical activities.
Qualifications:
- Ph.D. or Master's degree in Data Science, Statistics, Mathematics, Actuarial Science, Computer Science, or a related quantitative field.
- Minimum of 8 years of experience in data science, with a strong focus on the insurance or financial services industry.
- Proven expertise in developing and deploying predictive models using statistical and machine learning techniques (e.g., regression, classification, time series analysis, NLP, deep learning).
- Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (e.g., Pandas, NumPy).
- Strong knowledge of SQL and experience with database management.
- Familiarity with actuarial principles and insurance product lifecycles.
- Excellent analytical, problem-solving, and critical thinking skills.
- Exceptional communication and presentation skills, with the ability to explain complex models to diverse audiences in a remote setting.
- Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
- Ability to work independently and manage multiple projects effectively in a remote environment.
This advertiser has chosen not to accept applicants from your region.
5
Remote Senior Data Scientist - Financial Modeling
601 Southern, Southern
BHD60 Hourly
WhatJobs
Posted 21 days ago
Job Viewed
Job Description
Our client, a rapidly expanding fintech organization, is seeking a highly skilled and experienced Senior Data Scientist to lead their advanced financial modeling initiatives. This is a fully remote position, allowing you to leverage your expertise from anywhere. You will play a crucial role in developing sophisticated predictive models, driving data-driven decision-making, and enhancing our client's competitive edge in the financial services sector.
Responsibilities:
Qualifications:
This is an exceptional opportunity to make a significant impact in a remote capacity for a leader in financial technology. If you possess a passion for data and a track record of delivering impactful financial insights, we encourage you to apply.
Responsibilities:
- Design, develop, and implement complex statistical and machine learning models for financial forecasting, risk assessment, and fraud detection.
- Analyze large, intricate datasets to extract actionable insights and identify trends relevant to financial markets and customer behavior.
- Collaborate with cross-functional teams, including finance, product, and engineering, to define modeling requirements and integrate solutions.
- Build and maintain robust data pipelines and ETL processes for model training and deployment.
- Evaluate model performance, conduct A/B testing, and iterate on models to improve accuracy and efficiency.
- Communicate complex findings and recommendations clearly and concisely to both technical and non-technical stakeholders.
- Mentor junior data scientists and contribute to the team's technical growth.
- Stay current with the latest advancements in data science, machine learning, and financial analytics.
- Ensure data integrity, model explainability, and adherence to ethical data practices.
- Contribute to the strategic roadmap for data science initiatives within the organization.
Qualifications:
- Master's or Ph.D. in Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.
- Extensive professional experience as a Data Scientist, with a strong focus on financial modeling and analysis.
- Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas, NumPy).
- Deep understanding of statistical modeling, machine learning algorithms, and time-series analysis.
- Experience with SQL and working with large-scale relational and non-relational databases.
- Familiarity with cloud platforms (AWS, Azure, GCP) and big data technologies (e.g., Spark, Hadoop).
- Excellent problem-solving skills and the ability to translate business problems into data science solutions.
- Strong communication and presentation skills, with the ability to articulate technical concepts to diverse audiences.
- Proven ability to work independently and collaboratively in a remote team environment.
- Experience in the fintech or banking industry is a significant advantage.
This is an exceptional opportunity to make a significant impact in a remote capacity for a leader in financial technology. If you possess a passion for data and a track record of delivering impactful financial insights, we encourage you to apply.
This advertiser has chosen not to accept applicants from your region.
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6
Senior Insurance Data Scientist, Risk Modeling
1010 Al Daih, Northern
BHD125000 Annually
WhatJobs
Posted 22 days ago
Job Viewed
Job Description
Our client, a leading innovator in the insurance sector, is seeking an experienced Senior Data Scientist to join their fully remote, advanced analytics team. This role is pivotal in developing and refining sophisticated risk models that underpin the company's underwriting and pricing strategies. You will leverage vast datasets to extract actionable insights, build predictive models, and contribute to data-driven decision-making across the organization. Your responsibilities will include data exploration, feature engineering, model selection and validation, and the implementation of machine learning algorithms for risk assessment, fraud detection, and customer segmentation. The ideal candidate possesses a strong foundation in statistical modeling, machine learning techniques, and programming languages such as Python or R. Experience with large-scale data processing and cloud platforms (AWS, Azure, GCP) is highly desirable. A deep understanding of the insurance industry, including actuarial principles and common risk factors, will be a significant asset. You should be adept at communicating complex analytical findings to both technical and non-technical stakeholders, fostering a data-centric culture. This is a fully remote opportunity, requiring a proactive, self-motivated individual with excellent problem-solving skills and the ability to collaborate effectively within a distributed team. If you are passionate about applying advanced data science techniques to solve complex insurance challenges and thrive in a flexible, remote work environment, we encourage you to apply.
Responsibilities:
Responsibilities:
- Develop, implement, and validate advanced statistical and machine learning models for risk assessment and pricing.
- Conduct exploratory data analysis to identify trends, patterns, and insights within large insurance datasets.
- Design and engineer relevant features for predictive modeling.
- Evaluate and compare different modeling techniques to select the most appropriate solutions.
- Deploy models into production environments and monitor their performance.
- Collaborate with actuarial, underwriting, and product teams to understand business needs and translate them into analytical solutions.
- Communicate complex analytical findings and recommendations to stakeholders through clear reports and presentations.
- Stay current with the latest advancements in data science, machine learning, and insurance analytics.
- Mentor junior data scientists and contribute to team knowledge sharing.
- Master's or Ph.D. in Statistics, Data Science, Computer Science, Economics, or a related quantitative field.
- 5+ years of experience as a Data Scientist, with a significant focus on risk modeling or actuarial science.
- Proficiency in programming languages like Python or R, and relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with SQL and working with large, complex datasets.
- Strong understanding of statistical modeling, machine learning algorithms, and experimental design.
- Familiarity with insurance industry data and concepts is highly preferred.
- Experience with cloud platforms (AWS, Azure, GCP) and big data technologies is a plus.
- Excellent analytical, problem-solving, and communication skills for a remote setting.
This advertiser has chosen not to accept applicants from your region.
7
Lead Data Scientist - Financial Risk Modeling
300 Al Daih, Northern
BHD160000 Annually
WhatJobs
Posted 14 days ago
Job Viewed
Job Description
Our client is seeking an accomplished Lead Data Scientist to spearhead their financial risk modeling initiatives within the Banking & Finance sector. This is a critical, fully remote role where you will leverage advanced statistical techniques, machine learning, and big data technologies to develop sophisticated risk models. You will be responsible for designing, building, validating, and deploying predictive models that assess and mitigate various financial risks, including credit risk, market risk, and operational risk. The ideal candidate will possess a strong academic background in a quantitative discipline (e.g., Statistics, Mathematics, Computer Science, Physics) and a proven track record in applying data science to complex financial problems. Your responsibilities will include leading a team of data scientists, mentoring junior members, and collaborating closely with risk management, business intelligence, and IT departments. You will also be responsible for staying abreast of the latest advancements in data science and financial modeling, and identifying opportunities for innovation. Proficiency in programming languages such as Python or R, and experience with machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch) and big data platforms (e.g., Spark, Hadoop) are essential. Strong SQL skills and experience with data visualization tools are also required. Excellent communication and presentation skills are necessary to articulate complex findings to both technical and non-technical audiences. This role demands a self-starter with exceptional analytical and problem-solving abilities, capable of working independently and driving projects to completion in a remote environment. A Master's or Ph.D. in a relevant quantitative field is strongly preferred. Join a leading financial institution committed to leveraging data analytics for superior risk management and strategic decision-making. This is an unparalleled opportunity to shape the future of financial risk assessment from anywhere in the world, driving significant impact and growth. We offer a collaborative and intellectually stimulating remote work environment.
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8
Senior Data Scientist - Insurance Risk Modeling
60006 Saar, Northern
BHD135000 Annually
WhatJobs
Posted 17 days ago
Job Viewed
Job Description
Our client, a distinguished leader in the Insurance industry, is actively seeking a highly analytical and experienced Senior Data Scientist to join their fully remote team. This role is critical for developing and refining sophisticated risk models that underpin our underwriting, pricing, and claims management strategies. You will leverage advanced statistical techniques, machine learning, and vast datasets to drive informed decision-making and enhance our competitive advantage.
Responsibilities:
Responsibilities:
- Design, develop, and implement advanced statistical and machine learning models for insurance risk assessment, including predictive modeling, fraud detection, and customer lifetime value analysis.
- Analyze large and complex datasets to identify trends, patterns, and insights relevant to insurance operations and risk management.
- Collaborate with actuaries, underwriters, and product development teams to translate business needs into data-driven solutions.
- Build and maintain robust data pipelines and analytical frameworks to support ongoing modeling efforts.
- Evaluate the performance of existing models, identifying areas for improvement and implementing enhancements.
- Stay abreast of the latest advancements in data science, machine learning, and actuarial science, and champion their adoption where appropriate.
- Communicate complex findings and model methodologies clearly and concisely to both technical and non-technical stakeholders.
- Ensure all modeling activities comply with regulatory requirements and ethical best practices.
- Mentor junior data scientists and contribute to the growth of the data science community within the organization.
- Master's or PhD in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field.
- A minimum of 7 years of experience in data science, with a significant focus on risk modeling within the insurance or financial services sector.
- Expertise in programming languages such as Python or R, and proficiency with data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy).
- Strong experience with machine learning algorithms (e.g., regression, classification, clustering, deep learning) and relevant libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
- Familiarity with SQL and experience working with large relational databases.
- Knowledge of actuarial principles and insurance industry data is highly desirable.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and presentation skills, with the ability to convey complex technical concepts effectively.
- Proven ability to work independently and collaboratively in a fully remote, fast-paced environment.
This advertiser has chosen not to accept applicants from your region.
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