Senior Scientist, Scientific Computing

Johnson & Johnson Innovation; Hyderabad; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

Johnson & Johnson Innovation is seeking a Senior Scientist, Scientific Computing to advance statistical computing and AI-driven insights within Statistics & Decision Sciences. You will own end-to-end AI/ML development, collaborate with statisticians, and deploy scalable, compliant solutions across cloud and on-premises platforms.

You will design RAG pipelines, manage pipelines and training, and ensure reproducibility and data integrity across studies and trials.

Qualifications

• PhD in a quantitative field or Master’s with 3–5 years of software/ML engineering experience, including hands-on LLMs.
• Experience building production services in Python and R for data science workflows.
• Familiarity with AI/ML lifecycle and deployment in cloud environments.

Responsibilities

• Own end-to-end AI/ML layer architecture, evaluation, and deployment across platforms.
• Prototype and scale scientific computing tools for reproducibility and compliance.
• Design and maintain AI pipelines, agent workflows, and prompt strategies.
• Set up CI/CD, repositories, and development environments for SDS teams.
• Collaborate with statisticians and programmers; communicate complex results clearly.
• Lead MCP servers integration and data flow between tools and internal sources.

Skills

Python

R

LLM APIs

AI/ML deployment

AWS

Docker

CI/CD

Git

Data visualization

Education

PhD in Computer Science, Data Science, Statistics, Engineering or related

Tools

AWS

Azure

S3

EC2

Kubernetes

CI/CD pipelines

Job description

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function

Data Analytics & Computational Sciences

Job Sub Function

Biostatistics

Job Category

Scientific/Technology

All Job Posting Locations

Beerse, Antwerp, Belgium, High Wycombe, Buckinghamshire, United Kingdom, Hyderabad, Andhra Pradesh, India, Leiden, South Holland, Netherlands, Mumbai, India

Job Description

Senior Scientist, Scientific Computing

Position Summary

Statistics & Decision Sciences (SDS) is a function of Quantitative Sciences & Clinical Pharmacology. SDS comprises of Cardiopulmonary, Oncology, Immunology, Neuroscience, Medical Affairs, Post Approval Lifecycle Management, Discovery & Manufacturing Statistics, Statistical Modeling & Methodology & Consulting and Strategic Business & Computing Operations.

The SBCO organization applies deep understanding of drug development, statistics, scientific computing, business operations, and enabling technologies to deliver scalable, compliant, and high-value solutions for SDS. SBCO comprises three integrated units: Strategy & Business Operations (SBO), Scientific Computing Operations (SCO), and the SDS Centralized Administrative Network (SCAN).

The Senior Scientist, Scientific Computing provides technical and scientific computing support to advance statistical and strategic innovation, automation, and reproducibility across Statistics & Decision Sciences (SDS). The role helps ensure that platforms, tools, and data practices are robust, compliant, and aligned to business and regulatory needs.

The Senior Scientist, Scientific Computing, provides technical support and delivery for scientific computing and business capabilities within Statistics & Decision Sciences (SDS). The role collaborates with key stakeholders to drive and develop fit-for-purpose, compliant, and scalable solutions. Responsibilities include support for evaluation, integration, and lifecycle management of statistical and business analytical tools; establishing and maintaining validated data storage, archival, and data-flow strategies and effective training, adoption, and collaboration practices across SDS.

Principal Responsibilities

• Exhibits effective software expertise through applied experience, grounded in scientific and business principles with a proven record of effectively supporting strategic efforts. Demonstrates competence in utilizing computational tools to analyze and visualize data for research and business objectives related to studies, experiments, trials, and processes. This includes full proficiency in relevant computational and scripting tools, including artificial intelligence (AI).
• This role goes beyond model prototyping. You will own the AI/ML layer end to end, from architecture and evaluation to the cloud infrastructure it runs on. You’ll work closely with statisticians and programmers, so comfort with R/Python for statistical work and data visualization is important, not optional.
• Design and build RAG pipelines, agent workflows, and prompt/context strategies across our AI initiatives.
• Set up and maintain repositories, CI/CD pipelines, and development environments for the wider SDS team.
• Supports Scientific Software Packages, High Performance Computing (HPC) Hardware and platforms, communication tools, and standards and good practices documentation. Also supports business system and process improvement areas.
• Identifies and implements innovative tools and solutions in process automation and scientific computing domains. Identifies and implements advanced techniques to address complex project or program features. Proven ability in problem-solving and troubleshooting, including supporting strategic scenario planning, quantitative decision-making, and business support.
• Collaborates cross-functionally to identify and resolve issues. Successfully addresses business needs through enhanced insights, productivity, and efficiency. Advises management of opportunities to increase compatibility, interoperability, stability and usability of solution architecture.
• Demonstrates strong skills in building relationships across functions. Is accountable as a point of contact for a specific project or effort.
• Collaborates effectively with SDS colleagues and external partners to meet program needs. Works cross-functionally to identify and resolve issues.
• Shares knowledge within and across functions. Represents Statistics & Decision Sciences in cross-functional and intra-departmental teams or working groups pertaining to scientific or process initiatives. Builds cross-functional partnerships with internal colleagues and external partners (e.g., contractors, consultants) to achieve results for project-specific needs, focusing one enhancing communication, efficiency, and productivity.
• Supervise contractors/special assignment personnel/interns/co-ops as required.
• Exhibits strong written, oral, and interpersonal communication skills, and demonstrates proficiency in collaborating with by translating intricate technical concepts for drug research and development partners. Effectively communicates findings to program stakeholders and broader non-technical audiences with visuals and storytelling.
• Takes responsibility and accountability for the quality and timeliness of project deliverables as assessed by stakeholders from respective projects or programs. Follows best practices for Software Engineering, Project Management, and Data Integrity. Aligns with partners following best practices for Good Clinical, Manufacturing, Laboratory, or other pertinent GxP activities and requirements. Complies with organization and company standard operating procedures in a timely fashion, such as required training and project time reporting. Ensures that documents, programs, and all other deliverables are consistent and adhere to project and company standards.
• Stand up and manage MCP servers connecting AI tools to internal data sources and applications.

Qualifications

• PhD in in Computer Science, Data Science, Statistics, Computational Biology, Engineering or a related quantitative field or Master’s with 3 to 5 years of software/ML engineering experience, including 1 to 2+ years working hands-on with LLMs in production.

Technical Skills

• Strong Python; experience building production services, not just notebooks
• Working proficiency in R programming(or strong willingness/ability to read and work with R)
• Hands-on experience with LLM APIs (Anthropic, OpenAI, or similar) and at least one agent framework (e.g. LangGraph, LlamaIndex, or a custom framework)
• Databases
• Understanding of LLM failure modes (hallucination, context drift, prompt injection) and mitigation strategies.
• Hands-on AWS (S3, EC2, GPU instances) or Azure equivalent, including basic IAM/security and cost management
• Git-based workflows, CI/CD, containerization (Docker)
• Experience setting up MCP servers or comparable integration/orchestration tooling.

Preferred Skills

Advanced Analytics, Biostatistics, Clinical Trials, Collaboration, Consulting, Critical Thinking, Data Privacy Standards, Data Quality, Data Savvy, Digital Fluency, Good Clinical Practice (GCP), Quality Assurance (QA), Report Writing, Standard Operating Procedure (SOP), Statistical Analysis Systems (SAS) Programming, Statistics, Systems Development, Technologically Savvy