Senior Data Scientist
Role details
Job location
Tech stack
Job description
Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. You will enjoy the flexibility to telecommute* from anywhere within the U.S. as you take on some tough challenges., Lead the design, development, and deployment of applied machine learning solutions addressing complex business and clinical problems using large-scale healthcare data Own the end-to-end model lifecycle: problem framing, feature engineering, model development, evaluation, validation, explainability, deployment, and post-production monitoring Develop and review production-grade Python code following software engineering best practices (testing, modularization, version control, CI/CD) Architect scalable data science workflows using Python, SQL, and distributed data processing frameworks in cloud or enterprise environments Apply and advance classical ML, deep learning, time-series modeling, and survival analysis techniques based on business needs Ensure models are interpretable, explainable, and compliant with enterprise governance, regulatory, and ethical standards (e.g., bias, fairness, auditability) Partner with engineering, product, clinical, and business stakeholders to translate ambiguous problems into actionable analytical solutions Provide technical leadership and mentorship to senior and mid-level data scientists; set standards for modeling, experimentation, and code quality Review and approve modeling approaches, assumptions, and results; influence architectural and methodological decisions across teams Communicate insights, risks, and tradeoffs clearly to technical and executive audiences Stay current with emerging methods in applied ML, healthcare analytics, and MLOps, and drive adoption of best practices You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in., Overview: Role: Housekeeper Join Healthcare Services Group (HCSG) as a Housekeeper, where you will play a vital role in maintaining a clean and safe environment in a long-term …
- 5 days ago
Requirements
7+ years of experience building production-quality, maintainable, and testable code 7+ years of experience in machine learning and statistical modeling fundamentals, including: Feature engineering and selection Model training, tuning, and evaluation Model interpretability and explainability (e.g., SHAP, feature attribution) Hands-on experience with deep learning architectures where appropriate Strong applied experience with time-series analysis and survival analysis Experience with vibe coding tools, such as Cursor, Claude Code, and Windsurf 7+ years of experience in healthcare data literacy, including experience with: Claims, EHR, lab, and pharmacy data Coding systems such as ICD, CPT, NDC, SNOMED, and LOINC Interoperability standards such as FHIR and HL7 7+ years of experience leading complex applied data science initiatives from concept to production 7+ years of experience mentoring senior data scientists and elevate technical standards 7+ years of experience working in cross-functional environments with engineering, product, and business teams 7+ years of experience balancing model sophistication, interpretability, scalability, and business impact Advanced level proficiency in Python for data science and ML (Pandas, NumPy, scikit-learn, PyTorch or equivalent) Advanced level of SQL skills for complex data transformations and analytical workflows Preferred Qualifications: Experience with MLOps practices (deployment, monitoring, retraining, drift detection) Prior experience in regulated or highly governed environments Familiarity with cloud platforms and distributed computing (e.g., Spark, Databricks, AWS, GCP, Azure) Soft Skills: Excellent written and verbal communication skills, with the ability to convey technical concepts to non-technical stakeholders Ability to reason about data quality, missingness, bias, and confounding in healthcare datasets
Benefits & conditions
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $91,700 to $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
