Senior Data Scientist

🕒 October 30

🏈 Ohio – Remote

🏈 Ohio – Remote

💵 $132k - $165k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

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Gifthealth

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2020

🏥 Healthcare

📦 Logistics

💼 Consulting

💰 $40M Private Equity Round - GiftHealth on 2023-04

Healthcare • Logistics • Consulting

Gifthealth is a technology-enabled patient access and prescription fulfillment company that connects patients, prescribers, pharmacies, and pharmaceutical manufacturers through a unified digital platform. It streamlines enrollment, electronic benefits verification, e-prior authorization, and payment/affordability support while managing pharmacy fulfillment and patient support services. The platform also provides manufacturers with actionable data and insights on patient journeys and brand performance, driving faster, more reliable medication access.

📋 Description

• Own traditional machine learning models addressing operational and patient-outcome questions • Model patient refill, pharmacy switching, checkout, prior authorization, call volume, staffing demand, and distribution center throughput decisions • Drive patient outcomes and operational improvements through machine learning • Own evaluation mechanisms for reliable agentic AI workflows • Apply data-driven rigor to foundation model selection and parameter optimization • Partner with data engineers on feature pipelines • Source new data inputs and own modeling data end-to-end • Work within a data platform built on Snowflake, dbt, Terraform, and Looker • Define how models are evaluated, validated, documented, monitored, and retired • Document data science best practices • Mentor newer data scientists as the team grows • Support the AI/ML Engineering team and report to the Sr. Manager, AI/ML Engineering • Collaborate regularly with data engineers and the AI/ML Engineering team

🎯 Requirements

• Degree is optional; demonstrated capability is evaluated instead of credentials • Typically 4 to 7 years of experience, as a guide rather than a requirement • Experience building predictive models and shipping them into business processes • Experience owning post-launch model operations, including deployment, batch or real-time scoring, monitoring, or retraining • Strong SQL and Python • Comfortable working in a cloud warehouse and dbt, or able to learn quickly • Strong statistical judgment, including understanding validation, leakage, drift, and target selection • Serious experience with LLMs, including building evaluations and understanding hallucination risks • Demonstrated application of the stated skills • Independent judgment and mentoring ability • Ability to use AI tools while reading, auditing, and debugging generated code • Ability to work at a computer for extended periods • Effective verbal and written communication with data engineers and non-technical stakeholders • Ability to handle and access PHI in compliance with HIPAA, BAAs, masking, and role-based access requirements • Ability to read, audit, and debug code and models • Nice to have: Snowflake, especially Snowflake ML, Feature Store, Model Registry, and Snowpark • Nice to have: Healthcare, pharmacy, payer, or life-sciences data experience • Nice to have: Generative AI platforms such as Snowflake Cortex AI or Amazon Bedrock • Nice to have: Experience working with PHI under HIPAA and BAAs • Nice to have: Time series and operational forecasting • Nice to have: Survival analysis or treatment of censored data • Nice to have: Probabilistic record linkage or master data management • Nice to have: Experience introducing data science into a company without an existing data science practice

🏖️ Benefits

• Investment in education, upskilling, and career growth • Mentorship opportunities • Flexible schedule as needed for model monitoring, retraining, or evaluation work • Full-time employment • Standard business hours

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