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Senior Insurance Data Scientist

WhatJobs Direct

Remote · Nigeria Full-time Senior 1w ago

About the role

About

Our client is seeking a highly analytical and innovative Senior Insurance Data Scientist to join their fully remote team. This role is crucial for leveraging vast datasets to derive actionable insights, improve risk assessment models, enhance customer experience, and drive strategic decision‑making within the insurance industry. The ideal candidate will have a strong foundation in statistical modeling, machine learning, and data mining techniques, with a specific focus on insurance‑related challenges. You will be responsible for designing, developing, and implementing advanced analytical solutions that address complex business problems.

Responsibilities

  • Build predictive models for fraud detection, risk pricing, customer churn, and claims analysis.
  • Work with large, complex datasets, clean and transform data, and conduct exploratory data analysis to identify key trends and patterns.
  • Collaborate closely with actuaries, underwriters, and business stakeholders to understand their needs and translate them into data‑driven solutions.
  • Proactively identify new analytical opportunities, stay current with cutting‑edge data science techniques, and communicate complex findings clearly to both technical and non‑technical audiences.
  • Manage self‑direction and communication effectively in a fully remote setting.

Qualifications

  • Master's or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
  • Minimum of 6 years of experience as a Data Scientist, with a significant portion focused on the insurance industry.
  • Proven expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and data mining techniques.
  • Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (e.g., Pandas, NumPy).
  • Experience with SQL and working with relational databases.
  • Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
  • Strong understanding of insurance products, operations, and regulatory environments.
  • Excellent analytical, problem‑solving, and critical thinking skills.
  • Exceptional ability to communicate complex technical concepts to non‑technical stakeholders.
  • Experience with data visualization tools (e.g., Tableau, Power BI).
  • Ability to work independently and manage multiple projects effectively in a remote setting.
  • Strong attention to detail and commitment to data quality.

Closing

If you are a seasoned Data Scientist with a passion for transforming the insurance landscape through advanced analytics, this remote opportunity is perfect for you. Join our client and make a significant impact on their data‑driven initiatives.

Requirements

  • Proven expertise in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and data mining techniques.
  • Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (e.g., Pandas, NumPy).
  • Experience with SQL and working with relational databases.
  • Strong understanding of insurance products, operations, and regulatory environments.
  • Excellent analytical, problem-solving, and critical thinking skills.
  • Exceptional ability to communicate complex technical concepts to non-technical stakeholders.
  • Experience with data visualization tools (e.g., Tableau, Power BI).
  • Ability to work independently and manage multiple projects effectively in a remote setting.
  • Strong attention to detail and commitment to data quality.

Responsibilities

  • Building predictive models for fraud detection, risk pricing, customer churn, and claims analysis.
  • Working with large, complex datasets, cleaning and transforming data, and conducting exploratory data analysis to identify key trends and patterns.
  • Collaborating closely with actuaries, underwriters, and business stakeholders to understand their needs and translate them into data-driven solutions.
  • Identifying new analytical opportunities.
  • Staying current with cutting-edge data science techniques.
  • Communicating complex findings clearly to both technical and non-technical audiences.

Skills

AWS LambdaClusteringClassificationComputer ScienceData MiningData ScienceDeep LearningHadoopMachine LearningMathematicsNumPyPandasPower BIPythonRRegressionSparkSQLStatisticsTableau

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