Senior Scientist, Scientific Computing

8080-Johnson & Johnson Private Limited Legal Entity

Hyderabad

On-site

INR 2,500,000 - 5,000,000

Full time

6 days ago

Be an early applicant

Application generator

An application made for this job — a tailored resume and cover letter that speak straight to the posting.

Get past ATS filters

Job summary

Johnson & Johnson is seeking a Senior Scientist in Scientific Computing to advance statistics, AI/ML, and reproducible scientific computing within the SDS organization. You will collaborate with statisticians and programmers, owning the AI/ML layer end-to-end from architecture to cloud deployment.

You will work on evaluating, integrating, and lifecycle-managing statistical tools, establishing data storage, and enabling scalable, compliant solutions for drug research and development partnerships

Qualifications

PhD in Computer Science, Data Science, Statistics, Computational Biology, Engineering or related quantitative field, or Master’s with 3–5 years of software/ML engineering.
Proven ability with AI/ML workflows and production-grade software.
Experience with AI/ML pipelines, data handling, and scalable tooling.

Responsibilities

Own the AI/ML layer end to end from architecture to deployment.
Design and build RAG pipelines, agent workflows, and prompt strategies for AI initiatives.
Set up and maintain repositories, CI/CD pipelines, and development environments for SDS.

Skills

Python

LLM APIs

AWS

CI/CD

Docker

MCP servers

Education

PhD or Master’s with 3–5 years ML/Software

Tools

LLM APIs

MCP servers

Docker

Git + CI/CD

Job description

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions 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: Hyderabad, Andhra Pradesh, India

Job Description

Senior Scientist, Scientific Computing 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).

Position Summary

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.

Required Skills