REGISTRIEREN

Jobbörse

Finde Jobs in deiner Nähe – ob vor Ort, hybrid oder remote.
  • Ähnliche Jobs zu: Senior Data Scientist Advisor
XX
Senior Data ScientistJames Search Group • New York, New York, United States
Jetzt Bewerben
XX

Senior Data Scientist

James Search Group
  • US
    New York, New York, United States
  • US
    New York, New York, United States
Jetzt Bewerben

Über

Senior / Lead Data Scientist (P&C Insurance) Job type: Fully Remote | Full-Time
Base Pay Range $120,000.00/yr – $170,000.00/yr
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
Performance‑based bonus/variable compensation
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.
#J-18808-Ljbffr
  • New York, New York, United States

Sprachkenntnisse

  • English
Hinweis für Nutzer

Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klick auf „Jetzt Bewerben”, um deine Bewerbung direkt auf deren Website einzureichen.