4 Senior Data Scientist Insurance Analytics jobs in whatjobs
Senior Data Scientist - Insurance Analytics
Posted 20 days ago
Job Viewed
Job Description
Our client is revolutionizing the insurance industry through data-driven insights and is seeking a highly skilled Senior Data Scientist to join their remote-first team. This role is pivotal in leveraging advanced analytical techniques to drive strategic decisions, enhance customer experiences, and optimize business operations within the insurance sector. You will be responsible for the entire data science workflow, from problem definition and data extraction to model development, validation, and deployment. This includes building predictive models for risk assessment, fraud detection, customer churn, and pricing optimization. The ideal candidate will have a strong command of statistical modeling, machine learning algorithms, and programming languages such as Python or R. Experience with big data technologies and cloud platforms (e.g., AWS, Azure, GCP) is highly valued. You will work closely with business stakeholders to understand their challenges and translate them into data science solutions. Effective communication of complex analytical findings to both technical and non-technical audiences is essential. This position offers an exciting opportunity to work on challenging problems, contribute to groundbreaking innovations, and mentor junior data scientists within a collaborative remote environment. We are looking for a proactive individual with a passion for uncovering insights from data and a commitment to delivering measurable business impact. The ability to design and implement robust, scalable machine learning pipelines is crucial for success in this role.
Responsibilities:
Qualifications:
Responsibilities:
- Develop and implement advanced statistical and machine learning models for insurance applications (e.g., risk, fraud, pricing).
- Design and execute data mining strategies to extract valuable insights from large datasets.
- Collaborate with business units to define analytical problems and develop solutions.
- Build and deploy predictive models, ensuring their accuracy and performance.
- Perform rigorous model validation and A/B testing.
- Communicate complex analytical findings and recommendations to stakeholders.
- Mentor junior data scientists and share best practices.
- Stay abreast of the latest advancements in data science and AI.
- Contribute to the development of data infrastructure and tooling.
- Ensure data privacy and security compliance.
Qualifications:
- Master's or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
- Minimum of 5 years of experience in data science, with a focus on the insurance industry.
- Proficiency in Python or R, including relevant data science libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Strong experience with SQL and working with large, complex datasets.
- Familiarity with big data technologies (e.g., Spark, Hadoop) and cloud platforms (AWS, Azure, GCP).
- Deep understanding of various machine learning algorithms and statistical modeling techniques.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and presentation skills, with the ability to explain technical concepts to non-technical audiences.
- Experience with data visualization tools.
- Proven ability to work independently and as part of a remote team.
This advertiser has chosen not to accept applicants from your region.
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Senior Data Scientist - Insurance Analytics
Posted 20 days ago
Job Viewed
Job Description
Our client, a leading firm in the insurance sector, is seeking a highly skilled and experienced Senior Data Scientist to join their growing remote analytics team. This position offers the flexibility to work from anywhere, focusing on leveraging data to drive critical business decisions and enhance customer experiences. The ideal candidate will have a robust background in statistical modeling, machine learning, and data mining, with a proven ability to extract actionable insights from complex datasets. You will play a pivotal role in developing predictive models, optimizing risk assessment, and identifying opportunities for operational efficiency within the insurance lifecycle. This role requires a strong analytical acumen, excellent problem-solving skills, and a deep understanding of insurance industry challenges.
Key Responsibilities:
Qualifications:
Key Responsibilities:
- Develop, test, and deploy advanced statistical models and machine learning algorithms to address business problems in insurance.
- Analyze large datasets to identify trends, patterns, and correlations related to customer behavior, risk, and claims.
- Build predictive models for customer segmentation, churn prediction, fraud detection, and pricing optimization.
- Collaborate with actuaries, underwriters, and business stakeholders to understand their needs and translate them into data science solutions.
- Design and implement A/B tests and other experiments to evaluate the impact of data-driven strategies.
- Communicate complex findings and recommendations clearly and effectively to both technical and non-technical audiences.
- Contribute to the development of data infrastructure and best practices within the data science team.
- Stay current with the latest advancements in data science, machine learning, and artificial intelligence.
- Mentor junior data scientists and contribute to a culture of data-driven decision-making.
Qualifications:
- Master's or Ph.D. in Statistics, Data Science, Computer Science, Mathematics, or a related quantitative field.
- Minimum of 5 years of professional experience as a Data Scientist, with a strong emphasis on the insurance or financial services industry.
- Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (e.g., Pandas, NumPy).
- Expertise in machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch) and statistical modeling techniques.
- Strong SQL skills and experience working with large databases.
- Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
- Excellent problem-solving and critical thinking abilities.
- Superior communication and presentation skills.
- This is a fully remote role, supporting our business operations in **Nyeri, Nyeri, KE**.
This advertiser has chosen not to accept applicants from your region.
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Senior Data Scientist - Insurance Analytics
Posted 9 days ago
Job Viewed
Job Description
Our client, a leading innovator in the insurance sector, is seeking an exceptional Senior Data Scientist to join their fully remote team. This role is instrumental in driving data-informed decision-making across all aspects of the business, from product development and risk assessment to customer experience and fraud detection. The ideal candidate will possess a strong command of statistical modeling, machine learning algorithms, and data visualization techniques, with a proven track record of applying these skills to complex insurance-related problems. You will be responsible for extracting actionable insights from vast datasets, building predictive models, and communicating your findings to both technical and non-technical stakeholders. This is a unique opportunity to shape the future of insurance analytics and contribute to significant business growth.
Key responsibilities include:
Key responsibilities include:
- Developing and implementing advanced statistical models and machine learning algorithms for insurance risk assessment, pricing, and claims analysis.
- Performing complex data mining and exploratory data analysis to identify trends, patterns, and opportunities.
- Building predictive models for customer behavior, churn prediction, fraud detection, and underwriting optimization.
- Designing and conducting A/B tests and other experiments to evaluate the impact of new initiatives.
- Collaborating closely with actuaries, underwriters, claims adjusters, and product managers to understand business needs and deliver data-driven solutions.
- Creating clear and compelling data visualizations and dashboards to communicate insights to senior leadership.
- Mentoring junior data scientists and contributing to the team's technical growth.
- Staying abreast of the latest advancements in data science, machine learning, and AI, particularly within the financial services and insurance industries.
- Ensuring data quality, integrity, and adherence to regulatory requirements.
- Communicating technical findings and recommendations effectively to diverse audiences.
This advertiser has chosen not to accept applicants from your region.
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Senior Data Scientist - Insurance Analytics
Posted 1 day ago
Job Viewed
Job Description
Our client, a major player in the insurance industry, is seeking a highly skilled Senior Data Scientist to join their fully remote analytics team. This role is central to driving data-informed decision-making across the organization, particularly in areas of risk assessment, fraud detection, and customer behavior analysis. You will leverage advanced statistical modeling, machine learning techniques, and big data technologies to extract actionable insights from complex datasets. Responsibilities include developing and implementing sophisticated predictive models for risk pricing, claims forecasting, and customer segmentation; designing and executing A/B tests to evaluate new product features and marketing strategies; identifying opportunities for process improvement and cost reduction through data analysis; collaborating with actuarial, underwriting, and claims departments to understand business needs and translate them into analytical solutions; building and maintaining robust data pipelines and analytical tools; presenting complex findings and recommendations to both technical and non-technical audiences; staying current with the latest advancements in data science, machine learning, and insurance analytics; and mentoring junior data scientists. The ideal candidate will have a Master's or Ph.D. in a quantitative field such as Statistics, Computer Science, Mathematics, or Economics, coupled with at least 5 years of progressive experience in data science, with a strong focus on the insurance sector. Proficiency in programming languages like Python or R, SQL, and experience with big data platforms (e.g., Spark, Hadoop) and cloud environments (e.g., AWS, Azure) are essential. Expertise in machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and a solid understanding of insurance products and regulations are highly desirable. Exceptional problem-solving skills and the ability to communicate complex technical concepts clearly are critical.
This advertiser has chosen not to accept applicants from your region.
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