Senior Data Scientist

Versant Health•Troy, NY

21d•$170,000 - $180,000

About The Position

The Senior Data Scientist is a principal-level individual contributor responsible for architecting, delivering, and governing enterprise-grade advanced analytics and machine learning solutions that materially influence strategic decisions, financial performance, operational efficiency, and regulatory posture. This role operates at the intersection of data science, data engineering, cloud analytics platforms, and business strategy, serving as a technical authority and thought leader across complex, high-risk analytical initiatives—particularly within regulated healthcare environments. The Senior Data Scientist is accountable not only for model development, but for explainability, stability, auditability, and long-term operational viability of analytical solutions deployed at scale within the Microsoft data ecosystem.

Requirements

Master's degree in data science, statistics, mathematics, computer science, engineering, or related field required.
7–10+ years of progressive experience delivering advanced analytics or machine learning solutions in complex, data-rich environments.
Prior experience in healthcare analytics (payer, provider, life sciences, or regulated healthcare data domains).
Proven experience deploying production analytics or ML solutions supporting mission-critical business processes.
Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow where appropriate)
SQL (advanced T-SQL optimization, analytical patterns)
ML explainability and governance techniques (e.g., SHAP-style approaches, stability testing)
Deep, hands-on, production experience across sizable portion of the Microsoft analytics ecosystem, including: Microsoft Fabric (Lakehouse, Data Warehouse, Real-Time Analytics, Notebooks), Azure Synapse Analytics (dedicated & serverless SQL pools), Azure Data Factory (Fabric Data Pipelines), Azure Data Lake Storage, Azure Machine Learning (model training, deployment, monitoring), Power BI (semantic models, DAX optimization, executive dashboards), Microsoft Purview (data cataloging, lineage, classification)
HIPAA & Security Requirements

Nice To Haves

Prior acutrary experience a plus.

Responsibilities

Architect, design, and deploy advanced statistical, predictive, and machine learning solutions that support enterprise-level decision-making across healthcare, operations, finance, and customer/member domains.
Own end-to-end analytical solution lifecycle, including data discovery, feature engineering, modeling, validation, performance monitoring, retraining strategy, and retirement planning.
Serve as a technical authority on model explainability, fairness, robustness, and regulatory defensibility—particularly where ground truth or forward-looking forecasts are limited.
Design analytics solutions natively within the Microsoft cloud analytics stack, ensuring alignment to enterprise data architecture and governance standards.
Partner closely with executive stakeholders, data engineering leaders, and platform owners to translate complex business questions into high-impact, production-ready analytics.
Lead and influence analytics standards without direct authority.
Define best practices for: model documentation, audit artifacts, model risk management, stability analysis, reproducibility, and controlled experimentation.
Guide and review work produced by other data scientists, analysts, and vendors to ensure technical rigor and business relevance.
Present complex analytical findings to senior leadership using clear narratives, decision-oriented visuals, and quantified trade-offs.
Proactively identify analytical risks, data limitations, and downstream impacts of modeling decisions.
Continuously evaluate emerging tools, methodologies, and Microsoft platform capabilities to drive modernization and performance gains.