Senior Data Scientist

This is a fully remote position, open to applicants in North Carolina, +3 more states.

📋 Description

• Collaborate with internal stakeholders to translate business challenges into analytical or machine learning problems, establish success metrics, and define achievable project scopes.

• Create data products and workflows that support essential operations, from initial data discovery to production deployment.

• Transition and update workloads from R, Stata, and SAS to Python and Databricks.

• Design, train, and validate models for classification, regression, forecasting, clustering, and anomaly detection.

• Engineer features and develop reusable, governed feature pipelines on large datasets utilizing PySpark and SQL.

• Monitor experiments, register models, and manage model versions and promotions through MLflow.

• Deploy models for both batch scoring and real-time serving; automate retraining processes with scheduled jobs and CI/CD pipelines.

• Oversee production models for performance, data drift, and data quality; set thresholds and alerts accordingly.

• Spearhead client AI adoption, including use cases involving LLM and agentic applications such as RAG, document summarization, and classification.

• Assess LLM and agent outputs for accuracy, groundedness, and safety.

• Document models for governance and responsible AI review.

• Develop reference use cases accompanied by tutorials, reference code, and training materials.

• Conduct office hours and partner with client analysts and data scientists to enhance their skills.

• Present insights and model outcomes to both technical and non-technical audiences, including leadership.

⛳️ Requirements

• Bachelor’s degree in Engineering, Computer Science, Statistics, Mathematics, Systems, Business, or a related scientific or technical field, along with 15+ years of experience (or equivalent experience).

• Expertise in Python (pandas, NumPy, SciPy, scikit-learn) and advanced SQL (window functions, CTEs, query optimization) for data analysis.

• At least 2 years of practical experience with a leading cloud data platform such as Databricks, Azure, AWS, or GCP.

• Familiarity with the complete data science workflow, from dataset discovery and assessment to production deployment, including experiment tracking and model management using MLflow or similar tools.

• Strong foundation in traditional machine learning techniques: both supervised and unsupervised methods, gradient-boosted trees (XGBoost, LightGBM), model selection, cross-validation, and hyperparameter tuning.

• Proficient in applied statistics: hypothesis testing, regression, sampling, and experimental design.

• Experience working with large datasets in a distributed environment (Spark/PySpark).

• Strong model evaluation practices: selecting appropriate metrics, addressing class imbalance, preventing leakage, and interpreting model behavior (e.g., SHAP or feature importance).

• Working knowledge of large language models (LLMs) and agentic AI workflows, encompassing prompt design and RAG patterns.

• Version control experience with Git and collaborative development methodologies (code reviews, branching, testing).

• Capacity to communicate technical concepts to non-technical stakeholders and to transform vague requests into clearly defined deliverables.

• Must be a U.S. citizen.

• Must be able to obtain a public trust clearance.

• Must be eligible to work in the United States.

• Desired: 5+ years of experience as a data scientist, having successfully shipped multiple operational products.

• Desired: Experience working with Databricks on Azure, including Unity Catalog, Delta Lake, Databricks Jobs, and Databricks notebooks/Repos.

• Desired: MLOps experience throughout the lifecycle, including model serving, managed feature tables, CI/CD, production monitoring, model testing, automated retraining, lineage, and auditability.

• Desired: Familiarity with Azure AI services or Mosaic AI.

• Desired: Prior experience delivering products utilizing LLMs or AI agents, inclusive of evaluation and guardrails.

• Desired: Over 2 years of experience creating visual insights with Power BI, Databricks AI/BI dashboards, or Tableau.

• Desired: Previous experience with R, Stata, or SAS.

• Desired: Experience converting R, Stata, or SAS codebases to Python.

• Desired: Familiarity with VA or federal healthcare data and managing PHI/PII in accordance with federal privacy and security regulations.

• Desired: Understanding of federal AI governance and responsible AI practices.

• Desired: Experience in training or mentoring analysts and data scientists.

• Desired: Master's or PhD in a quantitative discipline.

🏝️ Benefits

• Competitive salary.

• Generous annual leave and paid holidays.

• Comprehensive group health and dental insurance plans.

• 401(k) plan with company matching.

• Life insurance and AD&D coverage.

• Continuous training and professional development opportunities.