Data Scientist f Submission Data and Content Generation & Reuse (AIDCG) - Pharma R&D

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The Position

Job Description

The Lead IT Data Scientist is responsible for architecting, leading, and delivering advanced AI and data science solutions that address complex business and scientific challenges within Pharma R&D. This role serves as a technical leader, guiding the design, development, deployment, and governance of enterprise-scale AI/ML systems while mentoring junior data scientists and driving innovation across the organization.

Operating in a highly regulated GxP environment, you will lead the development of next-generation AI-powered platforms and specialized autonomous agents supporting Analytical Data Scientists across the clinical data lifecycle. The role requires deep expertise in Generative AI, Agentic AI frameworks, multi-agent orchestration, Graph-based Retrieval-Augmented Generation (GraphRAG), Large Language Model Operations (LLMOps), and AI platform engineering. You will define technical strategy, establish best practices, and collaborate with cross-functional teams to ensure scalable, compliant, and business-aligned AI solutions.

Description Of The Area

The Clinical Submission Data and Content Generation & Reuse function focuses on transforming the creation, management, and reuse of clinical data and regulatory submission content through advanced digital capabilities and AI-driven automation. The organization develops structured content management platforms, reusable data and content assets, and intelligent agent ecosystems that support clinical submissions, regulatory compliance, and scientific communication.

The team is at the forefront of leveraging Generative AI, Agentic Workflows, Knowledge Graphs, and advanced analytics to improve quality, accelerate submission timelines, and enable data-driven decision-making across the clinical and regulatory landscape.

Job Responsibilities

Scope / Content LeadershipLead the architecture, development, and deployment of enterprise-grade AI/ML solutions and agentic systemsDrive multiple strategic data science initiatives simultaneously, ensuring alignment with business prioritiesDefine technical standards, reusable frameworks, and best practices for AI and machine learning developmentDesign and implement enterprise-wide data science frameworks, governance models, and best practices to ensure consistency, scalability, and operational excellence across AI initiativesMentor and guide data scientists, fostering technical excellence and innovation across the teamLead complex data science projects end-to-end, from problem definition and solution design through deployment, adoption, and measurable business impact Accountability / Problem SolvingSolve highly complex and ambiguous business problems using advanced statistical modeling, machine learning, and generative AI techniquesDesign and implement sophisticated multi-agent workflows using frameworks such as LangGraph and AWS AgentCoreLead development of intelligent automation solutions including autonomous code reviewers, clinical workflow copilots, AI-driven debugging assistants, and submission content generation agentsDrive model validation, monitoring, explainability, and AI governance practices in regulated environments Stakeholder ManagementPartner with senior business leaders, clinical experts, statisticians, and technology teams to identify strategic opportunities for AI adoptionTranslate complex analytical concepts into actionable business insights for executive and non-technical audiencesInfluence key stakeholders on AI strategy, roadmap prioritization, and solution adoptionWork closely with senior leadership to inform, shape, and influence strategic business decisions through data-driven insights, advanced analytics, and AI-enabled recommendations Impact / StrategyDefine and execute the technical roadmap for advanced analytics, Generative AI, and agentic AI capabilities within the functionLead high-impact projects that directly influence organizational objectives, innovation initiatives, and operational efficiencyEvaluate emerging technologies and recommend scalable solutions that advance business transformation Complexity / Product SizeWork with large-scale clinical, regulatory, and enterprise datasets across structured and unstructured formatsDesign scalable AI architectures supporting production-grade solutions with high reliability and compliance requirementsDrive optimization of existing models and establish frameworks for continuous improvement and performance monitoring Business / Technical AbilityDemonstrate deep expertise across multiple AI/ML domains including predictive modeling, NLP, knowledge graphs, GraphRAG, and agent-based systemsApply strong software engineering principles to develop secure, scalable, and maintainable AI productsLead technical decision-making related to model architecture, framework selection, cloud infrastructure, and deployment strategies

Qualifications

Education / Experience

Master's or PhD in Data Science, Computer Science, Statistics, Artificial Intelligence, Bioinformatics, Mathematics, or related quantitative discipline8-12 years of experience in Data Science, Machine Learning, Artificial Intelligence, Advanced Analytics, or similar domainsProven experience leading end-to-end AI/ML initiatives from ideation through production deployment and business adoptionExtensive experience leading complex data science projects from end-to-end and delivering significant, measurable business impactDemonstrated success in delivering enterprise-scale solutions that influence strategic business outcomesProven track record of partnering with senior executives and business leaders to drive data-informed strategic decision-makingExperience mentoring data scientists and providing technical leadership across cross-functional teamsExperience working within regulated environments such as Pharmaceutical, Healthcare, Life Sciences, or other compliance-driven industries is preferred

Technical Skills

Programming & Data Engineering

Expert-level proficiency in Python for AI/ML development, agent orchestration, backend services, and automation solutionsStrong hands-on expertise in R for clinical statistical programming, NextGen programming frameworks (e.g., Admiral), and analysis workflowsWorking knowledge of SAS and clinical programming standards is desirableStrong understanding of software engineering concepts, APIs, microservices, CI/CD pipelines, GitOps, and testing frameworks

Generative AI & Agentic Systems

Deep expertise in Large Language Models (LLMs), Prompt Engineering, Fine-tuning, Agentic AI, and AI application architectureExtensive experience with LangChain, LangGraph, CrewAI, AWS AgentCore, AutoGen, Semantic Kernel, and Model Context Protocol (MCP)Proven experience designing multi-agent architectures, autonomous workflows, reasoning systems, and human-in-the-loop AI solutionsStrong understanding of AI safety, governance, observability, evaluation frameworks, and responsible AI practices

RAG, Knowledge Graphs & Search

Advanced experience in Retrieval-Augmented Generation (RAG), Agentic RAG, Hybrid Search, and GraphRAG implementationsExpertise in chunking strategies, embedding models, vector databases, semantic retrieval, re-ranking techniques, and metadata-driven searchExperience with Neo4j, Knowledge Graphs, graph databases, ontologies, and enterprise search architectures

Machine Learning & Advanced Analytics

Strong expertise in supervised and unsupervised learning, predictive modeling, NLP, deep learning, and time-series analysisExperience with TensorFlow, PyTorch, Scikit-learn, XGBoost, and modern ML frameworksStrong foundation in experimental design, statistical inference, model evaluation, and explainable AI techniques

Cloud & MLOps / LLMOps

Experience deploying AI solutions on AWS, Azure, or GCP platformsStrong expertise in MLOps and LLMOps practices including model lifecycle management, monitoring, evaluation, governance, and automationExperience with containerization technologies such as Docker, Kubernetes, and cloud-native AI deployments

Data Visualization & Reporting

Expertise in developing impactful visualizations and dashboards using tools such as Tableau, Power BI, R Shiny, Plotly, or Python visualization librariesAbility to communicate complex analytical insights through compelling storytelling and executive-ready presentations

Additional Qualifications

Exceptional communication and presentation skills with the ability to influence senior stakeholders and executive leadershipStrong leadership and mentoring capabilities with experience building high-performing teamsAbility to balance strategic thinking with hands-on technical executionDemonstrated innovation mindset and ability to identify emerging technology opportunitiesStrong collaboration skills across business, clinical, regulatory, and technology organizationsDemonstrated experience establishing enterprise-wide data science standards, operating models, governance practices, and reusable frameworks across large organizationsExperience supporting GxP-compliant systems, validation processes, and regulatory requirements related to AI solutions is highly desirable

Shift: CET time zone

#Hyderabad2026

Who we are

A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact.

Let’s build a healthier future, together.

Roche is an Equal Opportunity Employer.