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Data Science Lead

Texnere Americas IncNew York, NY🇺🇸United StatesPosted Oct 1, 2026

Why This Role Stands Out

Leverage your extensive healthcare ML expertise to lead impactful initiatives in patient outcomes and drive innovation at a respected company, with the flexibility of a remote work environment. This role is ideal for a seasoned data scientist who thrives on end-to-end ownership and stakeholder collaboration, offering significant opportunities for growth and influence. Apply today to shape the future of healthcare data science!

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
New York, NY, United States
Posted
17 hours ago
Machine LearningPharmacySourcing

Job Description

Job Title: Principal / Lead Data Scientist – Healthcare ML

Location: Remote
Experience: 10+ Years
Employment Type: W2

Job Overview

We are seeking a hands-on Principal / Lead Data Scientist with strong healthcare machine learning experience to lead an end-to-end initiative focused on adverse events (AEs) in specialty patients.

The ideal candidate will be deeply technical while also demonstrating strong ownership, solution-design, stakeholder-management, and delivery skills. This is an end-to-end leadership role, requiring the ability to independently drive the initiative from problem framing and data exploration through model development, validation, deployment, and business adoption.

Candidates should have authentic and verifiable experience working with healthcare, specialty pharmacy, patient outcomes, claims, adherence/persistence, clinical events, or related healthcare datasets.

Key Responsibilities

  • Own the end-to-end data science and machine learning workstream from problem definition through production delivery.

  • Partner with clinical, product, operations, and business stakeholders to translate business and clinical objectives into actionable ML solutions.

  • Define modeling objectives around adverse events, therapy discontinuation, clinically meaningful events, and intervention timing.

  • Design ML solutions covering data sourcing, feature engineering, modeling, evaluation, explainability, deployment,

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