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Senior Manager Data Science

Novartis
Novartis
6+ years
Not Disclosed
Hyderabad
1 May 6, 2026
Job Description
Job Type: Full Time Education: Bachelor’s or Master’s Degree in: Data Science Computer Science Statistics Mathematics Artificial Intelligence Engineering Life Sciences Or related quantitative disciplines Skills: Apache Spark, Artificial Intelligence (AI), Big Data, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategies, Data Visualization, Machine Learning (ML), Master Da

Senior Manager – Data Science

Location: Hyderabad (Office)
Job Type: Full-Time
Experience Required: Minimum 6+ Years in Data Science or Advanced Analytics
Application Deadline: May 20, 2026
Industry: Pharmaceutical / Healthcare / Life Sciences


Job Overview

We are seeking an experienced and strategic Senior Manager – Data Science to lead advanced analytics initiatives, machine learning projects, and enterprise data management operations within a fast-paced healthcare and life sciences environment. The ideal candidate will leverage data science, artificial intelligence, machine learning, and statistical modeling to solve complex business challenges, generate actionable insights, and support innovation across multiple business domains.

This role is ideal for professionals with strong expertise in data science, AI, predictive analytics, and stakeholder management who can transform structured and unstructured data into impactful business intelligence solutions.


Key Responsibilities

Data Science & Advanced Analytics

  • Analyze complex business problems and develop integrated analytical solutions using:
    • Machine Learning
    • Artificial Intelligence (AI)
    • Deep Learning
    • Statistical Modeling
    • Predictive Analytics
  • Build scalable analytical frameworks to support decision-making and automation.
  • Develop machine learning algorithms and advanced statistical models for healthcare and life sciences data.
  • Automate data management workflows, reporting systems, and recurring analytics processes.

Data Management & Governance

  • Manage the enterprise data lifecycle including:
    • Data acquisition
    • Data enrichment
    • Data quality management
    • Data retention and governance
  • Ensure availability of accurate, clean, and business-ready data across organizational systems.
  • Improve data quality standards and governance practices across analytical programs.

Business Collaboration & Stakeholder Management

  • Collaborate with:
    • Cross-functional teams
    • Internal business stakeholders
    • External partners
  • Translate analytical findings into business recommendations through:
    • Smart data visualization
    • Business storytelling
    • Executive presentations
  • Support strategic business decisions with data-driven insights and intelligence.

Research & Innovation

  • Research emerging technologies, scientific software, and advanced analytical approaches.
  • Explore new algorithms, statistical techniques, and AI methodologies applicable to healthcare and pharmaceutical domains.
  • Identify and evaluate research articles and industry innovations for potential business implementation.

Project & Team Management

  • Independently manage project execution, timelines, budgets, and operational risks.
  • Anticipate business changes and proactively manage stakeholder expectations.
  • Lead or mentor small teams of data scientists and analysts where applicable.
  • Provide coaching, technical guidance, and support to junior team members.

Required Qualifications

Educational Qualifications

  • Bachelor’s or Master’s Degree in:
    • Data Science
    • Computer Science
    • Statistics
    • Mathematics
    • Artificial Intelligence
    • Engineering
    • Life Sciences
    • Or related quantitative disciplines

Preferred Qualifications

  • Master’s Degree or PhD in:
    • Data Science
    • Artificial Intelligence
    • Machine Learning
    • Statistics
    • Computational Biology
    • Bioinformatics
    • Healthcare Analytics
  • Certifications in:
    • Machine Learning
    • AI & Deep Learning
    • Cloud Data Platforms
    • Data Engineering
    • Advanced Analytics
  • Experience in pharmaceutical, healthcare, clinical research, or life sciences industries preferred.
  • Exposure to Generative AI (GenAI), NLP, and advanced predictive analytics solutions is highly preferred.