Data Scientist (Local Candidates Only)

Data Scientist II

South San Francisco, CA

Contract: 4 Months

Overview

We are seeking a Senior Data Scientist (Level II) to support high-impact AI/ML initiatives within a regulated environment. This role will focus on advancing targeting models and delivering scalable, production-ready solutions that drive business outcomes.

The ideal candidate brings strong technical depth, hands-on model development experience, and the ability to operate independently while collaborating across cross-functional teams.

Key Responsibilities

Model Development & Optimization

Lead the design, development, and optimization of machine learning models to improve targeting accuracy and business performance

Apply advanced Machine Learning and Deep Learning techniques to refine existing models and develop new solutions as needed

Feature Engineering & Data Preparation

Design and build scalable feature pipelines, transforming raw and complex datasets into high-quality model inputs

Work with large, messy datasets (e.g., claims data) while ensuring data integrity and usability

Production & Pipeline Scalability

Transition analytical models and scripts into robust, production-ready pipelines

Ensure code quality, documentation, and adherence to engineering and data science best practices

Support model deployment, monitoring, and ongoing performance improvements

Cross-Functional Collaboration & Insight Translation

Partner with data science, analytics, and business teams to translate business problems into technical solutions

Communicate model methodologies, assumptions, and results clearly to non-technical stakeholders

Qualifications Required

Master s or PhD in Data Science, Computer Science, Statistics, or a related field

Minimum 5+ years of hands-on experience in data science and machine learning model development

Proven track record of taking models from ideation through production deployment

Strong proficiency in Python, SQL, and AWS

Deep expertise in Machine Learning and/or Deep Learning techniques

Experience working with large-scale, complex datasets in collaborative environments

Preferred

Experience within healthcare, pharmaceutical, or other highly regulated industries

Hands-on experience with claims data or similarly complex, regulated datasets

Strong understanding of data privacy, compliance, and governance requirements

Experience with MLOps practices, including pipeline automation, deployment, and monitoring