Senior Data Scientist (Level II)

Senior Data Scientist (Level II) ROCGJP00040352 * Hourly pay: $75/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.