Staff Data Scientist

This is a fully remote position, open to applicants in Massachusetts.

📋 Description

• Develop configuration-driven machine-learning pipelines that train, select, score, and produce predictions from extensive longitudinal datasets.

• Transform claims, EHR, laboratory, and online behavioral-intent data into forecasts regarding healthcare utilization and the likelihood of preventive care enrollment.

• Create automated feature engineering and model selection processes for customer-specific models without the need for bespoke engineering.

• Identify modeling enhancements that can be applied consistently across various customer implementations.

• Implement and uphold data science components utilized by Forward Deployed Data Scientists in client deployments.

• Turn pilots and one-time proofs into scalable capabilities that remain effective across multiple clients.

• Establish the modeling benchmarks for client deployments and take responsibility for enhancements that can be generalized across different implementations.

• Occasionally interact with design-partner clients while primarily functioning in an applied, production-focused, non-client-facing capacity.

• Engage as a hands-on architect and builder; this role does not focus on research or management.

⛳️ Requirements

• Proven experience in delivering uplift, survival, or propensity models that have influenced organizational spending or outreach strategies.

• Background in transitioning pilots or proofs of concept into repeatable products that have been successful with multiple clients.

• Strong expertise in data science related to segmentation, campaign optimization, and identification strategies for uplift estimations.

• Capability to justify modeling decisions, critically assess models, and opt for simpler alternatives when suitable.

• Proficient in Python, pandas, scikit-learn, PySpark, and Airflow.

• Familiarity with model tracking and deployment tools such as MLflow or SageMaker.

• Competence in executing models at scale in AWS utilizing S3, Glue, EMR, MWAA, and SageMaker.

• Knowledge of healthcare or life sciences is a valuable asset.

• Awareness of HIPAA, healthcare compliance, and data governance frameworks is a plus.

• Experience in designing pilots and efficacy studies linked to business outcomes is advantageous.

• Background in building internal platforms or frameworks is beneficial.

🏝️ Benefits

• No specific benefits, perks, or compensation details provided.