Senior Data Scientists Analytics Leads

Role: Senior Data Scientists / Analytics Leads

Location: NJ/NYC/Charlotte NC/Columbus OH/Washington DC area/Malvern PA/Boston
Salary Range: $120000 - $150000 a year

Must Have Technical/Functional Skills

10 years in data science advanced analytics or applied statistics including 3 years leading analytical workstreams or mentoring data scientists. Must have personally built and validated predictive models; BI-only leadership is not sufficient.

Strong Python and SQL including pandas NumPy scikit-learn and XGBoost or LightGBM. PySpark for larger datasets and experience with environments such as Databricks SageMaker or Vertex AI are useful not required.

Solid statistics: hypothesis testing linear and logistic regression time-series methods sampling and clear communication of uncertainty.

Model development for at least one BFSI use case such as credit risk fraud/AML alert prioritization propensity/churn collections or forecasting. Choose validation and metrics appropriate to the problem (e.g. out-of-time tests AUC/KS for scorecards precision/recall for alerts MAE for forecasts).

Experience measuring business impact with A/B tests where feasible or with defensible observational approaches such as matched cohorts difference-in-differences or controlled pre/post comparisons; not every method is required.

Explainability and model governance: use SHAP or similar techniques assess bias where relevant and document assumptions limitations and validation. For US banking models familiarity with SR 11-7 expectations is useful; credit-decision reason codes apply only to relevant credit use cases.

Production awareness: Git code review reproducible pipelines unit and data tests MLflow tracking and handoff to ML engineering for batch scoring or APIs with monitoring such as PSI and performance drift.

Clear presentation of results: KPI definitions visuals and decision rules or score cut-offs that business teams can act on. Power BI or Tableau is a plus.

Practical GenAI use: applying LLMs to classify summarize or extract data from unstructured text (e.g. complaints KYC documents) and evaluating output quality. LLM infrastructure experience is not required.

Client-facing leadership: frame ambiguous problems agree on outcomes review code and results and guide a small team; experience coordinating across time zones is useful when delivery is distributed.