Job Title: Analyst - Data Engineer
Shift: 2 pm to 11 pm IST
Location: Manyata Tech Park, Bangalore.
Are you ready to dive into the world of commercial analytics and make a real impact Data Engineer or MLOps & AI Engineer is an incredible opportunity within the Data Science & Advanced Analytics team to support the transformation of AI/ML for Alexion's Rare Disease Unit by crafting, developing, and fielding data science solutions that drive impact for patients. This role works between traditional ML engineering and autonomous AI. It involves crafting, deploying, and managing classical machine learning systems and AI workflows that improve commercial efficiency across the US rare disease portfolio.
The primary focus will be collaborating with data scientists, and insights & analytics to build production-grade analytics infrastructure on Snowflake and Cortex AI — from predictive patient identification models and field force alert engines to agentic workflows that autonomously surface insights and recommend actions. This position ensures that ML models and AI agent systems are reproducible, compliant, performant, and scalable throughout their lifecycle. A strong focus is placed on data quality, monitoring, governance, and agent-executable system design. .
ML & Data Engineering
Model Lifecycle Management: Develop and maintain pipelines to transition models from experimentation to production, including packaging, CI/CD, automated testing, and deployment. Support model serving for patient identification, adherence prediction, Next-Best-Action engines, and competitive intelligence models on Snowflake and Cortex AI.
Data Pipeline Development: Design robust batch and streaming data workflows integrating specialty pharmacy, hub/PSP, CRM (Veeva), syndicated (IQVIA, MMIT), claims, and Model N data within Snowflake. Define and manage feature sets, lineage, and reuse to support AI/ML initiatives across the rare disease portfolio.
Production Operations & Monitoring: Ensure reliability and scalability of ML systems; Establish monitoring for model performance, data drift, bias, and service health. Monitor data quality across rare disease data feeds where small population sizes amplify the impact of anomalies.
Agentic AI & Agent Systems Engineering
Agent Workflow Design: Collaborate with data scientists and commercial stakeholders to decompose complex business workflows into agent-executable workstreams on Cortex AI. Determine which components are best suited for agent execution versus human data science judgment and define the boundaries between them.
Author structured coding instructions that translate commercial analytics requirements into precise agent directives with clear acceptance criteria.
Build agentic AI systems that autonomously detect anomalies in commercial data (competitive switching, patient discontinuation signals, payer access changes), generate hypotheses, and push recommended actions to stakeholders and CRM systems.
Model, Agent & Data Governance:



Ensure all AI/ML outputs are explainable, auditable, and compliant with HIPAA/PHI, GDPR, FDA promotional regulations, and REMS requirements. Enforce secrets management, role-based access control, network policies, and data protection for agents operating on sensitive healthcare and commercial data within the enterprise perimeter.

Multi-functional Partnership: Work closely with data scientists, commercial analysts, and collaborators across Brand, Market Access, Patient Services, and Field teams. Establish testing frameworks for both traditional ML models and agent-generated code. Design validation pipelines with automated quality gates including type checking, linting, integration tests, and contract tests.
Coordinate releases with commercial operations and IT; Essential Skills/Experience
Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field, or equivalent experience.
Experience: 3–6+ years in MLOps, Data Engineering, or ML Platform roles with a proven track record of deploying ML solutions at scale. At least 2+ years building complex data science or large-scale analytics solutions.
Programming: Proficiency in Python and SQL; familiarity with TypeScript/JavaScript or a systems language (Go, Rust). Experience with TDD, CI/CD pipelines, and code quality standards.
CI/CD & Infrastructure: Experience with CI/CD tools (e.g., GitHub Actions, Azure DevOps), containerization (Docker), and cloud infrastructure concepts.
ML Tools: Hands-on experience with model packaging and serving frameworks (e.g., Data Technologies: Proficiency with Snowflake (including Snowpark and Snowpark Container Services), distributed processing (Spark), and data orchestration (Airflow).
AI/Agent Tools: Hands-on experience with AI coding tools (Claude Code, GitHub Copilot, Cursor, or equivalent) and Cortex AI or comparable LLM serving platforms. Understanding of data privacy and security in healthcare; experience with secrets management, audit controls, and compliance frameworks (HIPAA, SOC2, 21 CFR Part 11).
Systems Thinking: Ability to design for how components interact at scale across both traditional ML infrastructure and agentic AI architectures.
Desirable Skills/Experience
Domain Experience: Knowledge of pharmaceutical commercial analytics in rare disease or specialty pharma — HCP/HCO targeting, patient identification, call planning, demand forecasting, specialty pharmacy data, hub/PSP operations, and omnichannel measurement.
Rare Disease Data Proficiency: Experience with IQVIA (LAAD, Symphony, NPA), Veeva CRM, MMIT, Model N, specialty pharmacy dispense data,



claims/RWD, and EMR/EHR data in small-population, high-value-per-patient environments.
Experience designing multi-agent workflows, agent orchestration patterns, and autonomous systems for enterprise applications. Performance & Scalability: Experience with high-throughput inference, batch scoring at scale, low-latency APIs, and horizontal scalability for agent workloads.
Experience integrating with Snowflake, Veeva, Salesforce, Microsoft 365, and ServiceNow APIs to enable end-to-end automation.
able to present complex findings to both technical and non-technical audiences. This role is at the center of that shift for Alexion's US Commercial organization — building the engineering foundation that makes both classical ML models and agentic AI systems reliable, auditable, and effective enough to operate at enterprise scale in a regulated rare disease environment. You will be instrumental in delivering the Data Science & Advanced Analytics capabilities that help Alexion find undiagnosed patients, optimize the rare disease field force, and drive commercial performance across a portfolio of life-changing therapies.
That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not versatile. We balance the expectation of being in the office while respecting individual flexibility. The Company will not make decisions about employment, training, compensation, promotion, and other terms and conditions of employment based on race, color, religion, creed or lack thereof, sex, sexual orientation, age, ancestry, national origin, ethnicity, citizenship status, marital status, pregnancy, (including childbirth, breastfeeding, or related medical conditions), parental status (including adoption or surrogacy), military status, protected veteran status, disability, medical condition, gender identity or expression, genetic information, mental illness or other characteristics protected by law. Alexion provides reasonable accommodations to meet the needs of candidates and employees. To begin an interactive dialogue with Alexion regarding an accommodation, please contact [HIDDEN TEXT]. The Company will not make decisions about employment, training, compensation, promotion, and other terms and conditions of employment based on race, color, religion, creed or lack thereof, sex, sexual orientation, age, ancestry, national origin, ethnicity, citizenship status, marital status, pregnancy, (including childbirth, breastfeeding, or related medical conditions), parental status (including adoption or surrogacy), military status, protected veteran status, disability, medical condition, gender identity or expression, genetic information, mental illness or other characteristics protected by law. Alexion provides reasonable accommodations to meet the needs of candidates and employees. To begin an interactive dialogue with Alexion regarding an accommodation, please contact [HIDDEN TEXT].

📌 Data Scientist, Data Analyst & Data Engineer (Bengaluru)
🏢 Alexion Pharmaceuticals
📍 Bengaluru