Lead Data Scientist

Hi There,

Greetings from Sightspectrum LLC..!!

I hope you doing well, Please find the below job description if you're comfortable share me your updated resume and contact details asap.

Authorized to work in the United States without sponsorship

Title: Lead Data Scientist

Location: Philadelphia, PA(Hybrid)

Duration: 6+ Months

Healthcare exp mandatory for both the roles.

Key Characteristics:

• An independent workstream owner who combines strong scientific judgment with hands-on delivery
• A strategic problem-solver who connects modeling decisions to underwriting outcomes and measurable economic value
• An influential collaborator who aligns Underwriting, Business, Product, and Engineering without relying on formal authority
• An effective communicator who explains technical trade-offs, risks, and business impact in a way that enables confident decisions across technical and business audiences
• A collaborative builder who contributes reusable components, documentation, and practical improvements to shared standards

Required Skills & Qualifications:

• Bachelor's or master's degree in Statistics, Data Science, Computer Science, Mathematics, Engineering, or a related quantitative field; an advanced degree is a plus
• 8+ years in data science, machine learning, statistics, actuarial analytics, including substantial work with healthcare, pharmacy, insurance risk, or sensitive longitudinal data and a proven record of independently owning models or analytical workstreams end to end
• Advanced Python and SQL, with experience in scikit-learn, XGBoost, GBMs, or comparable frameworks. Experience using PySpark or comparable distributed-computing tools to work with structured and unstructured data at scale is preferred; PyTorch experience is a plus
• Deep expertise in Supervised and Unsupervised Machine Learning methods, explainability, statistical distributions, rare-event and high-cost modeling, calibration, and optimization
• Proven ownership of production models and the MLOps lifecycle on AWS or a comparable cloud platform, including Git-based version control, testing, deployment, monitoring, retraining, rollback, documentation, and responsible AI/model-governance practices.
• Familiarity with Kedro or a similar pipeline framework is a plus. Experience with LLMs, prompt engineering, RAG, embeddings, vector DB, or agentic frameworks is helpful but not required.
• Strong business acumen and judgment, with the ability to connect analytical outputs to measurable business outcomes, influence cross-functional decisions, and navigate trade-offs among model quality, risk, cost, scalability, and time to value.