Sharp Decisions

Senior Data Scientist II

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist II, offering a 4-month contract at $79.39/hr in South San Francisco, CA. Requires a Master's/PhD, 5+ years in data science, proficiency in Python, SQL, AWS, and experience in regulated industries, preferably healthcare.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
632
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🗓️ - Date
April 30, 2026
🕒 - Duration
3 to 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
South San Francisco, CA
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🧠 - Skills detailed
#Python #Datasets #Data Science #Computer Science #Deep Learning #Statistics #Data Privacy #AI (Artificial Intelligence) #ML (Machine Learning) #Monitoring #AWS (Amazon Web Services) #"ETL (Extract #Transform #Load)" #SQL (Structured Query Language) #Scala #Documentation #Model Deployment #Compliance #Deployment #Automation #Data Integrity
Role description
Data Scientist II 94080, South San Francisco, California, United States- Hyrbid Pay - 79.39/hr on W2 Contract of 4 months with possible extension 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 & OptimizationLead 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 ScalabilityTransition 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 TranslationPartner 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 • RequiredMasters 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 • PreferredExperience 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 • What Were Looking ForA self-driven, senior-level contributor who can lead model development efforts and influence technical direction • Someone who thrives in a team environment and contributes to shared goals without needing sole ownership • A candidate who balances technical excellence with business impact, delivering solutions that are both scalable and meaningful • Additional NotesThis is a Level II role, requiring demonstrated depth in both technical execution and real-world application of AI/ML solutions • Candidates must be comfortable working in a fast-paced, collaborative, and regulated environment