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Hyderabad, Telangāna, India
Actively hiring, first seen by us 10 hours agoEmployment type in the employer’s posting: Regular / PermanentFrom the employer’s posting
You will define technical strategy, establish best practices, and collaborate with cross-functional teams to ensure scalable, compliant, and business-aligned AI solutions.
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
Master's or PhD in Data Science, Computer Science, Statistics, Artificial Intelligence, Bioinformatics, Mathematics, or related quantitative discipline.
Strong understanding of software engineering concepts, APIs, microservices, CI/CD pipelines, GitOps, and testing frameworks.
Deep expertise in Large Language Models (LLMs), Prompt Engineering, Fine-tuning, Agentic AI, and AI application architecture.
Strong expertise in supervised and unsupervised learning, predictive modeling, NLP, deep learning, and time-series analysis.
Experience deploying AI solutions on AWS, Azure, or GCP platforms.
Expertise in developing impactful visualizations and dashboards using tools such as Tableau, Power BI, R Shiny, Plotly, or Python visualization libraries.
Experience working within regulated environments such as Pharmaceutical, Healthcare, Life Sciences, or other compliance-driven industries is preferred.
Experience supporting GxP-compliant systems, validation processes, and regulatory requirements related to AI solutions is highly desirable.
Education / Experience - Master's or PhD in Data Science, Computer Science, Statistics, Artificial Intelligence, Bioinformatics, Mathematics, or related quantitative discipline. - 8-12 years of experience in Data Science, Machine Learning, Artificial Intelligence, Advanced Analytics, or similar domains.
A healthier future drives us to innovate.
In the employer’s words · Read in context
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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Early. Similar jobs usually come down between day 8 and day 59.
From 11,542 similar postings that came down. Coming down is not always a hire.
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Programming & Data Engineering - Expert-level proficiency in Python for AI/ML development, agent orchestration, backend services, and automation solutions. - Strong hands-on expertise in R for clinical statistical programming, NextGen programming frameworks (e.g., Admiral), and analysis workflows.
Data Visualization & Reporting - Expertise in developing impactful visualizations and dashboards using tools such as Tableau, Power BI, R Shiny, Plotly, or Python visualization libraries. - Ability to communicate complex analytical insights through compelling storytelling and executive-ready presentations.
- Expert-level proficiency in Python for AI/ML development, agent orchestration, backend services, and automation solutions. - Strong hands-on expertise in R for clinical statistical programming, NextGen programming frameworks (e.g., Admiral), and analysis workflows. - Working knowledge of SAS and clinical programming standards is desirable.
- Strong hands-on expertise in R for clinical statistical programming, NextGen programming frameworks (e.g., Admiral), and analysis workflows. - Working knowledge of SAS and clinical programming standards is desirable. - Strong understanding of software engineering concepts, APIs, microservices, CI/CD pipelines, GitOps, and testing frameworks.
- Solve highly complex and ambiguous business problems using advanced statistical modeling, machine learning, and generative AI techniques. - Design and implement sophisticated multi-agent workflows using frameworks such as LangGraph and AWS AgentCore. - Lead development of intelligent automation solutions including autonomous code reviewers, clinical workflow copilots, AI-driven debugging assistants, and submission content generation agents.
- Deep expertise in Large Language Models (LLMs), Prompt Engineering, Fine-tuning, Agentic AI, and AI application architecture. - Extensive 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 solutions.
Cloud & MLOps / LLMOps - Experience deploying AI solutions on AWS, Azure, or GCP platforms. - Strong expertise in MLOps and LLMOps practices including model lifecycle management, monitoring, evaluation, governance, and automation.
- Strong expertise in MLOps and LLMOps practices including model lifecycle management, monitoring, evaluation, governance, and automation. - Experience with containerization technologies such as Docker, Kubernetes, and cloud-native AI deployments. Data Visualization & Reporting
- Expertise in chunking strategies, embedding models, vector databases, semantic retrieval, re-ranking techniques, and metadata-driven search. - Experience 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 analysis. - Experience with TensorFlow, PyTorch, Scikit-learn, XGBoost, and modern ML frameworks. - Strong foundation in experimental design, statistical inference, model evaluation, and explainable AI techniques.
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New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.
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
1. Scope / Content Leadership
2. Accountability / Problem Solving
3. Stakeholder Management
4. Impact / Strategy
5. Complexity / Product Size
6. Business / Technical Ability
Qualifications
Education / Experience
Technical Skills
Programming & Data Engineering
Generative AI & Agentic Systems
RAG, Knowledge Graphs & Search
Machine Learning & Advanced Analytics
Cloud & MLOps / LLMOps
Data Visualization & Reporting
Additional Qualifications
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.
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Hyderabad, Telangāna, India
RAG, Knowledge Graphs & Search - Advanced experience in Retrieval-Augmented Generation (RAG), Agentic RAG, Hybrid Search, and GraphRAG implementations. - Expertise in chunking strategies, embedding models, vector databases, semantic retrieval, re-ranking techniques, and metadata-driven search.
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