Job
Description
Core Responsibilities
Own end-to-end delivery for assigned client projects across clinical data management, analytics, data science, and information management.Lead sprint planning, effort estimation, resource allocation, risk/issue management, and status reporting; ensure on-time and on-budget outcomes.Perform hands-on solutioning and execution (e.g., gathering business requirements, writing data pipelines, standards mapping, model building, dashboarding etc.) while guiding junior team members.Collaborate with client stakeholders (ClinOps, Biometrics, Safety, Medical Affairs, R&D IT) to align scope, requirements, acceptance criteria, and success metrics.Ensure compliance with GxP, 21 CFR Part 11, data privacy, and Axtrias GenAI/InfoSec policies when applicable.Contribute to capability buildingdevelop PoCs, POVs, case studies, delivery playbooks, and reusable accelerators for the Clinical Solutions COE.Support pre-salessolution outlines, effort/rate cards, proposal inputs, demos, and bid defenses.Report on portfolio healthutilization, margins/P&L drivers, delivery risks, and upcoming opportunities; escalate proactively.
Domain Experience Strong understanding of clinical trial lifecycle (Phase I"“IV) and core functionsClinical Operations, Biometrics/Statistical Programming, Drug Safety/Pharmacovigilance, and Medical Affairs.Hands-on work with clinical systems/data sourcesEDC (e.g., Medidata Rave, Veeva Vault CDMS), CTMS, IRT/RTSM, ePRO/eCOA, LIMS/Labs, and real-world data (EHR/EMR).Working knowledge of data standardsCDISC (CDASH, SDTM, ADaM), HL7/FHIR, LOINC; familiarity with audit readiness and submission workflows.Experience delivering clinical insightsenrollment tracking, protocol compliance, KRI/KPI reporting, adverse event analysis, site performance, and patient journey analytics.Working knowledge of AI/ML/NLP and GenAI concepts and their use cases in clinical domain with at least basic understanding of how these advanced analytics solutions work, what are their advantages and their challenges
Technical Skills Data engineering & analyticsPython/PySpark, SQL; orchestration on DatabricksCloud & data platformsAzure/AWS/GCP; data warehousing (e.g., Snowflake/Azure SQL); governance, lineage, and quality frameworks.VisualizationPower BI, Tableau, or Spotfire for clinical dashboards and executive reporting.Modeling & AIFamiliarity with classical ML (classification, regression, time-series, clustering), applied NLP and LLM/GenAI concepts (RAG, prompt design, evaluation).Project tools & methodsAgile/Scrum, JIRA/Confluence, MS Project/Smartsheet; strong documentation and estimation practices.
Soft Skills Client-facing communication with the ability to translate business needs into technical deliverables and measurable outcomes.People leadershipmentoring, performance feedback, delegation, and conflict resolution.Structured problem-solving, ownership mindset, and proactive risk management.Stakeholder management across onshore/offshore teams; ability to thrive in fast-paced, multi-project environments.
Qualifications Bachelors or Masters in Engineering, Computer Science, Statistics, Data Science, Life Sciences, or related field.At least 14 years of relevant experience across clinical data management/analytics/data science/data engineering; prior people-management experience preferred (4 years).Demonstrated track record delivering complex clinical data/analytics projects with high billability and quality.Certifications are a plusSAS, AWS/Azure, PMP/CSM, or similar.
