Senior Analyst (Medical Analytics) – ML Solution Owner

Are you ready to own high-impact ML solutions that guide medical strategy and accelerate decisions across our enterprise? You will lead production-grade analytics products in this role. These products extract signals from complex data to guide Medical, Commercial, Clinical Operations, and other teams. This helps drive faster, more consistent decisions that benefit individuals we serve and the organization.

You will translate real collaborator needs into scalable, secure solutions that combine robust engineering with advanced ML and generative AI. Join us at a pivotal moment as we invest in automation, modern data platforms and intelligent products to power the next chapter of growth. Would you thrive leading a multidisciplinary team to deliver tools that clinicians and leaders trust every day?

• Solution Ownership & Delivery: Act as the primary owner for assigned analytics and ML solutions, ensuring end-to-end delivery with high quality and agility; collaborate with partners to translate business needs into scalable, production-ready solutions; architect and lead all aspects of data pipelines, ML models and application workflows; maintain detailed documentation, business logic mapping and release notes; ensure compliance with data governance, privacy and security standards.
• Machine Learning & Advanced Analytics: Lead the building, creation and assessment of ML models for predictive analytics, classification and regression, NLP (topic modeling, summarization, extraction), recommendation engines and time-series forecasting; drive experimentation, testing, model optimization and explainability; leverage LLMs and generative AI for automation, summarization and insight extraction; evaluate and integrate new ML libraries, frameworks and platforms.
• Application Development & UI Engineering: Lead development of web-based UIs, dashboards and decision-support tools using Replit; Python with Flask/FastAPI; React, Streamlit or Dash; partner with application engineers to build end-to-end user experiences that integrate ML outputs; ensure applications are responsive, intuitive and performance-optimized.
• Team Leadership & Mentorship: Lead a team of six mid-level and junior data analysts, data scientists and application engineers; provide daily mentorship, code reviews, technical coaching and priority setting; foster an environment of creativity, ongoing development and high technical standards; coordinate workload planning, delivery timelines and critical issue management.
• Data Engineering & Integration: Guide develop of data pipelines, feature engineering workflows and cloud-based integrations; work with engineers to connect to structured and unstructured datasets (CSV, Excel, APIs, Databricks, SQL databases); ensure data quality, versioning and reproducibility.
• Collaborator Management & Communication: Act as the main point of contact for business partners on solution scope, achievements, risks and timelines; present analyses, model outcomes and product demos to leadership teams; influence decision-making through clear, actionable communication.
• Innovation & Continuous Improvement: Evaluate new technologies (LLMs, MLOps, AutoML, similarity search databases, Vibe Coding, advanced application frameworks); proactively propose POCs, quick prototypes and new analytics capabilities with measurable business value; drive adoption of modern development practices (CI/CD, GitHub workflows, model monitoring).

• Bachelor’s or master’s degree in computer science, Engineering, Data Science, Statistics, or related fields.
• 8–10 years of experience in analytics, machine learning, or solution delivery.
• Proven experience leading small to medium technical teams.

• Strong programming skills in Python (pandas, scikit‑learn, numpy, spaCy, transformers).
• Experience in ML model development, deployment, and monitoring.
• Strong knowledge of SQL and at least one cloud platform (Azure preferred).
• Experience with Databricks, PySpark, or equivalent big‑data engines.
• Ability to build applications using Replit, Streamlit, Flask/FastAPI, or React.
• Familiarity with healthcare/pharma datasets (IQVIA, EMR, claims, real‑world evidence).

• Strong understanding of solution architecture, software development lifecycle, and delivery governance.
• Ability to translate business needs into technical requirements.
• Strong documentation, estimation, scoping, and dependency‑management skills.

• Excellent communication, collaborator management, and mentorship capabilities.
• Ability to present insights and technical concepts to non‑technical audiences.
• Strong problem‑solving skills with a bias toward action and innovation.
• Ability to manage multiple projects simultaneously.

• Experience deploying ML models via containers, serverless functions, or MLflow.
• Knowledge of MLOps, CI/CD workflows, GitHub Actions.
• Hands‑on experience with LLMs, prompt engineering, and generative AI tools.
• Exposure to next‑gen development tools (Vibe Coding, AI‑assisted app development).
• Experience with NLP models for summarization, named entity recognition, Q&A systems.
• Knowledge of oncology, medical affairs, or commercial pharma analytics.
• Certifications in AI/ML, cloud, or data engineering.

Here you will help shape a tech-enabled enterprise where ambitious ideas become real solutions that speed decisions and free our scientists and clinicians to focus on what matters most—patients. We combine new data science with disciplined engineering. We bring diverse experts together to challenge assumptions and move quickly. We invest in modern automation to turn insight into action. You will join a global, collaborative network that values kindness alongside ambition, gives you the trust and accountability to own outcomes, and backs your curiosity with the scale and support to learn, experiment and deliver impact that’s felt well beyond your team.