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Senior Data Scientist (Level II) ROCGJP00040352 Hourly pay: $50-$60/hr Worksite: Leading biotechnology company (South San Francisco, CA 94080 – Hybrid – 3 days onsite) W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL 40 hours/week, 4 Month Assignment A leading biotechnology company is 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. Senior Data Scientist (Level II) Responsibilities: Lead the design, development, and optimization of machine learning and deep learning models to improve targeting accuracy and business performance. Design and build scalable feature pipelines, transforming large, complex datasets (e.g., claims data) into high-quality model inputs while ensuring data integrity. Develop and maintain production-ready data science solutions by transitioning analytical models into robust, scalable pipelines. Ensure code quality, documentation, and adherence to data science and engineering best practices. Support model deployment, monitoring, and continuous performance optimization. Partner with cross-functional teams and communicate methodologies, assumptions, and results clearly to both technical and non-technical stakeholders. Senior Data Scientist (Level II) Qualifications: 5+ years of hands-on experience in data science and machine learning model development. Master’s or PhD in Data Science, Computer Science, Statistics, or a related field. Proven track record of taking models from ideation through production deployment. Strong proficiency in Python, SQL, and AWS. Expertise in Machine Learning and/or Deep Learning techniques. Experience working with large-scale, complex datasets in collaborative environments. Experience within healthcare, pharmaceutical, or other highly regulated industries is preferred. Hands-on experience with claims data or similarly complex, regulated datasets is preferred. Strong understanding of data privacy, compliance, and governance requirements is preferred. Experience with MLOps practices, including pipeline automation, deployment, and monitoring, is preferred. Shift: 8:00 am to 5:00 pm (flexibility is required). On-site work: Monday, Tuesday, and Wednesday. (H)
