> Markdown version of [/jobs/ext/4702529-data-scientist-ii](https://www.wearedevelopers.com/jobs/ext/4702529-data-scientist-ii). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist II - **Company:** TALENTBURST - **Location:** South San Francisco, CA, United States - **Experience:** Expert - **Contract:** Temporary to permanent - **Skills:** Computer-Aided Design, Artificial Intelligence, Big Data, Software Quality, Data Integrity, Python (Programming Language), Machine Learning, Software Deployment, SQL Databases, Feature Engineering, Delivery Pipeline, Deep Learning, Build Management, Information Technology, Machine Learning Operations - **Published:** November 13, 2026 - **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=3068105088-2 ## About the Role The ideal candidate brings strong technical depth, hands-on model development experience, and the ability to operate independently while collaborating across cross-functional teams., * 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, A 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 Notes This 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 ## Description Data Scientist II ROCGJP Contract: 4 months Hybrid- M, Tues, Wed in-office 8am-5pm (flexibility needed) Interview process: In-person- 2 hrs & 15 mins l HackerRank (SQL & Python), technical ( ML techniques and AI solution design) interview / follow up interview (same day), 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., * 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