Data Scientist (Hybrid)

NYCM InsuranceTown of Edmeston, NY
$86,136 - $143,560Hybrid

About The Position

The Data Scientist independently applies advanced analytics and machine learning techniques to solve complex business problems and support organizational decision-making. This role is responsible for developing and maintaining predictive models, analyzing complex datasets, and delivering actionable insights aligned with business objectives. The Data Scientist collaborates with cross-functional stakeholders to support analytical initiatives and recommend data-driven approaches to business challenges. This position may provide technical guidance to Associate Data Scientists and supports analytical best practices within the department.

Requirements

  • Bachelor’s degree in applied mathematics, data science/analytics, computer science, statistics, or related field, and 4 years of experience in insurance, analytics or data science.
  • Proficiency in SQL, Python or R (Python preferred), and machine learning techniques.
  • Strong analytical, problem-solving, and organizational skills.
  • Ability to work independently and collaboratively within cross-functional teams.
  • Ability to explain technical concepts and analytical findings to non-technical audiences.
  • Understanding of statistical analysis, model evaluation, and responsible modeling practices.

Nice To Haves

  • Experience with data visualization tools such as Tableau preferred.
  • Familiarity with software engineering, cloud platforms, or database systems is a plus.

Responsibilities

  • Design, develop, test, deploy, and maintain predictive and analytical models.
  • Perform advanced exploratory analysis, feature engineering, model evaluation, and statistical analysis to support analytical initiatives.
  • Manage model lifecycle activities including validation, monitoring, documentation, and periodic retraining to ensure model effectiveness and reliability.
  • Collaborate with data engineers and business partners to support scalable analytical workflows and processes.
  • Design and evaluate experiments (e.g., A/B tests) to measure model and business performance.
  • Analyze complex datasets to develop actionable insights and recommendations that support operational and business decisions.
  • Support the identification of analytical opportunities and contribute to data-driven solutions for business challenges.
  • Document analytical processes, model assumptions, and results to support reproducibility and governance standards.
  • Contribute to knowledge sharing and provide guidance to Associate Data Scientists as appropriate.
  • Stay informed on emerging data science tools, techniques, and industry best practices.
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