2 Lead Data Scientist Insurance Analytics jobs in whatjobs
Lead Data Scientist - Insurance Analytics
Posted 11 days ago
Job Viewed
Job Description
Our client, a rapidly growing insurance provider, is looking for an accomplished Lead Data Scientist to spearhead their advanced analytics initiatives. This role is entirely remote, offering you the chance to leverage your expertise in data science and machine learning to drive strategic decisions within the insurance sector from anywhere in Kenya. You will be responsible for developing sophisticated predictive models, uncovering key insights from vast datasets, and translating complex findings into actionable business strategies. The ideal candidate possesses a strong blend of technical proficiency, statistical rigor, and business acumen, with a proven ability to lead projects and mentor junior team members. This position will be crucial in enhancing risk assessment, fraud detection, customer segmentation, and optimizing pricing models.
Responsibilities:
Qualifications:
Join us in transforming the insurance landscape from Embu, Embu, KE and beyond. If you are a data-driven leader ready to make a significant impact, apply today.
Responsibilities:
- Develop and implement advanced statistical models and machine learning algorithms for insurance applications (e.g., risk modeling, claims prediction, fraud detection).
- Lead the end-to-end data science project lifecycle, from problem definition and data collection to model deployment and performance monitoring.
- Extract, clean, and preprocess large, complex datasets from various sources within the insurance domain.
- Identify opportunities to leverage data analytics to improve business processes, product offerings, and customer experience.
- Collaborate closely with actuaries, underwriters, marketing, and IT teams to integrate data-driven insights into business operations.
- Mentor and guide a team of data scientists, fostering a culture of innovation and continuous learning.
- Communicate complex analytical findings and recommendations clearly and effectively to stakeholders at all levels, including senior management.
- Stay current with the latest advancements in data science, machine learning, and artificial intelligence, and explore their applicability to the insurance industry.
- Develop and maintain data pipelines and reporting dashboards for key performance indicators.
- Ensure the ethical and compliant use of data in all analytical endeavors.
Qualifications:
- Master's or Ph.D. in Statistics, Data Science, Computer Science, Mathematics, or a related quantitative field.
- 5+ years of professional experience in data science, with a significant focus on the insurance industry.
- Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, Pandas).
- Strong understanding of statistical modeling, machine learning techniques (regression, classification, clustering, time series analysis), and experimental design.
- Experience with SQL and working with large databases.
- Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
- Excellent problem-solving abilities and a strong analytical mindset.
- Demonstrated leadership skills and experience managing projects or teams.
- Exceptional communication and presentation skills.
- Knowledge of insurance products, regulations, and actuarial principles is highly desirable.
Join us in transforming the insurance landscape from Embu, Embu, KE and beyond. If you are a data-driven leader ready to make a significant impact, apply today.
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Lead Data Scientist, Insurance Analytics
Posted today
Job Viewed
Job Description
Our client, a pioneering insurance provider leveraging advanced data analytics, is seeking a talented and visionary Lead Data Scientist to spearhead our analytics initiatives. This position is fully remote, allowing you to contribute your expertise from anywhere. You will be responsible for developing and implementing sophisticated machine learning models and statistical techniques to drive strategic decisions across underwriting, claims, fraud detection, and customer behavior analysis. Your role will involve defining the data science roadmap, leading a team of data scientists, and collaborating closely with business stakeholders to identify opportunities where data can create significant value. The ideal candidate will possess a Ph.D. or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline, coupled with a strong track record of applying data science in the insurance industry. Proven experience in leading data science projects and mentoring junior team members is essential. You should be proficient in programming languages like Python or R, and have hands-on experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) and big data technologies (e.g., Spark, Hadoop). A deep understanding of statistical modeling, predictive analytics, and data mining techniques is required. You will also be responsible for communicating complex findings and insights to both technical and non-technical audiences, translating data-driven results into actionable business strategies. This role demands exceptional problem-solving skills, creativity, and the ability to work independently in a remote setting. You will be instrumental in shaping the future of data-driven decision-making within our organization, contributing to enhanced risk management, improved operational efficiency, and superior customer experiences. We value innovation, collaboration, and a passion for extracting meaningful insights from complex datasets to drive business success in the insurance sector.
This advertiser has chosen not to accept applicants from your region.
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