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Senior Data Scientist

James Search Group
Department:Data Analysis
Type:REMOTE
Region:USA
Location:United States
Experience:Mid-Senior level
Estimated Salary:$120,000 - $180,000
Skills:
PYTHONPANDASNUMPYSCIKIT-LEARNXGBOOSTLIGHTGBMTENSORFLOWPYTORCHDATABRICKSMLFLOWGITHUBSQLMACHINE LEARNINGDATA SCIENCEARTIFICIAL INTELLIGENCEMLOPSSTATISTICAL MODELINGDEEP LEARNINGNLP
👁️ Views: 11🚀️ Applied: 0
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Job Description

Posted on: July 27, 2025

Senior / Lead Data Scientist (P&C Insurance)

Fully Remote | Full-Time

Partnering with a Leading P&C Insurance Carrier

James Search Group is proud to partner with a high-performing Property & Casualty insurance carrier that is deeply investing in Data Science, Machine Learning (ML), and Artificial Intelligence (AI) to transform how insurance is priced, underwritten, and serviced. We’re seeking a Senior / Lead Data Scientist to join their centralized Data & ML/AI department and take a key role in building scalable, production-grade models that drive enterprise decision-making.

This is a hands-on and strategic role where you'll help shape the carrier’s approach to predictive modeling, optimization, and data-driven automation. You’ll collaborate across actuarial, underwriting, product, claims, and data engineering teams to identify high-impact problems and bring elegant ML solutions to life.

Office Locations (Optional Hybrid):

This is a remote-first position, but you can also work from one of the carrier’s multiple U.S. office locations

What You’ll Do:

  • Lead the design, development, and deployment of predictive models and machine learning pipelines across the insurance value chain.
  • Partner with stakeholders to scope high-value use cases in pricing, risk segmentation, underwriting automation, claims triage, fraud, retention, and more.
  • Own model lifecycle management from ideation through to deployment and monitoring in production.
  • Mentor junior data scientists, establish coding and modeling best practices, and participate in peer reviews.
  • Collaborate with data engineers and ML engineers to scale models using a modern MLOps stack.
  • Translate technical results into actionable insights for non-technical stakeholders.

What You Bring:

  • 5–8+ years of hands-on experience in Data Science or ML Engineering, with a strong portfolio of deployed models.
  • Deep understanding of statistical modeling, machine learning algorithms (e.g., tree-based models, ensemble methods, NLP, deep learning), and model evaluation techniques.
  • Advanced programming skills in Python, and experience with data manipulation libraries (e.g., pandas, NumPy), machine learning frameworks (e.g., scikit-learn, XGBoost, LightGBM), and deep learning tools (e.g., TensorFlow, PyTorch).
  • Experience with Databricks, MLflow, GitHub, and MLOps practices for productionization of models.
  • Strong SQL skills and ability to work with large, complex datasets.
  • Ability to communicate technical results clearly to cross-functional teams and business stakeholders.
  • Bachelor’s, Master’s, or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or a related field.

Bonus Points For:

  • Prior experience in the insurance industry, particularly P&C, working with claims, pricing, or underwriting data.
  • Familiarity with regulatory modeling standards (e.g., explainability, fairness).
  • Exposure to Hex, Arize, or similar tools for monitoring and visualization.
  • Experience with time series forecasting or geospatial modeling.

What’s In It for You:

  • Competitive base salary
  • Performance-based bonus/variable compensation
  • Comprehensive benefits, including:
  • Medical, dental, and vision insurance
  • 401(k) with company match
  • Generous PTO
  • Wellness and mental health support programs

This is a rare opportunity to lead cutting-edge Data Science work at a modern insurance organization where innovation is a priority.

If you’re excited to build models that go into production and directly shape customer and business outcomes — we’d love to connect.

Originally posted on LinkedIn

Apply now

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👁️ Views: 11🚀️ Applied: 0
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