Lead design, development, and production deployment of ML/DL models for targeting in a regulated biotech environment. Build scalable feature pipelines, prepare large complex datasets, ensure production-grade pipelines and monitoring, collaborate with cross-functional teams, and communicate model results to business stakeholders.
Our client, a world leader in biotechnology and life sciences, is looking for a “Senior Data Scientist" based out in South San Francisco, CA.
Job Duration: Long Term Contract (Possibility Of Extension & FT Conversion)
Rate: $75-$78/hr on W2 (DOE)
Company Benefits: Medical, Dental, Vision, Paid Sick leave, 401K
Job Summary
This role is to support high-impact AI/ML initiatives within a regulated environment and 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
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