Back
Strong Tier-1 brand and metro Hyderabad location increase candidate density, but specialized ML/data skills narrow the pool.
Core ML and data-engineering skills are transferable, though life-sciences preference increases specialization sensitivity.
Explicit 7-11 years plus mandated ML, PySpark, AWS, and data platform skills enforce stringent shortlisting filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and maintain scalable data pipelines and platforms for advanced analytics and AI applications with end-to-end ownership of performance, reliability, and governance.
Collaborate with data scientists, analysts, and business stakeholders to translate requirements into production-grade ML pipelines and act as a strategic advisor on data capabilities.
Participate in project planning, delivery, and cross-team collaboration within a matrix organizational structure to align functional and project goals.
Bachelor’s degree in Information Technology, Computer Science, or a related Technology field.
7-11 years of experience developing data pipelines and data infrastructure, preferably in drug development or life sciences context.
Strong programming skills in Python (including PySpark) and SQL with experience integrating ML models into production systems.
Residency within commuting distance of Hyderabad; hybrid work model requiring 3 days onsite presence.
Deep expertise in cloud platforms and data engineering, especially AWS (S3, IAM) and cloud data warehouses (Redshift, Snowflake, etc.).
Hands-on experience with experiment design and validation methodologies tailored for data enrichment and ML pipeline performance assessment.
Experience working in complex, matrixed global organizations and collaborating across data science, analytics, and business teams.