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:

Data Science

Job Category:

Scientific/Technology

All Job Posting Locations:

Beerse, Antwerp, Belgium, Cornellà de Llobregat, Barcelona, Spain, Madrid, Spain, Spring House, Pennsylvania, United States of America

Job Description:

Johnson & Johnson Innovative Medicine is seeking a Senior Data Scientist dedicated to our Small Molecule Discovery organization. This role sits within our Data Science team and partners closely with medicinal chemists, automation scientists, data engineers, computational scientists, and technology teams to ensure that small-molecule discovery data are transformed into trusted, reusable, AI-ready assets.

The role operates at the intersection of scientific discovery, data science, and scientific data engineering. You will help shape how molecular, synthesis and purification, and assay data are represented, connected, and leveraged to support scientific decision-making, advanced analytics, machine learning, and emerging AI capabilities throughout the discovery lifecycle.

Why this role matters: Small Molecule Discovery generates large volumes of complex and interconnected data across design, synthesis, purification, characterization, and testing workflows. Realizing the full value of these data requires more than traditional analytics. It requires deep understanding of how scientific workflows generate data, how those data should be modeled and governed, and how they can be transformed into reusable assets for decision support, machine learning, and AI-enabled discovery.

This role serves as a critical bridge between scientific workflows and modern data platforms, ensuring that discovery data can be effectively leveraged to accelerate insight generation, improve data quality, and enable next-generation AI applications developed by our partners in our In Silico Discovery.

Position Summary

As a Senior Data Scientist, Small Molecule Discovery, you will design and develop data assets, analytical solutions, and scientific data workflows to support discovery research across the Design-Make-Test-Analyze cycle.

You will work closely with discovery scientists, automation teams, and technology partners to transform complex scientific data into scalable, well-governed, and AI-ready resources. You will bring deep understanding of small-molecule discovery data and modern data science practices to help establish robust foundations for analytics, machine learning, and digital laboratory initiatives.

Key Responsibilities

Scientific Data Products & Analytics

• Design, develop, and maintain high-quality data assets that support small-molecule discovery workflows.
• Transform molecular, synthesis and purification, and assay data into reusable datasets that support scientific decision-making and machine learning applications.
• Partner with scientists and technology teams to define data requirements, business rules, and analytical use cases.
• Develop scalable analytical workflows using modern cloud data platforms and scientific computing tools.
• Apply data science methodologies to extract insights from complex discovery datasets.

Discovery Data & AI Readiness

• Ensure scientific data are structured, documented, and represented in ways that support advanced analytics and AI applications.
• Contribute to the development of data standards, metadata practices, and data quality frameworks for discovery data.
• Partner with data engineering teams to ensure discovery data products are scalable, traceable, and reproducible.
• Support the creation of model-ready datasets for machine learning and scientific AI initiatives.
• Evaluate emerging opportunities to apply AI and advanced analytics within discovery workflows.
• Scientific Partnership & Technical Leadership
• Serve as a trusted technical partner to medicinal chemists, automation scientists, and in silico discovery teams.
• Translate scientific workflows and requirements into computational and data solutions.
• Contribute to best practices in scientific computing, data management, and reproducible research.
• Mentor colleagues on modern data science approaches and scientific data practices.
• Foster collaboration across scientific, technical, and data-focused teams.

What Success Looks Like

How the role builds an essential part of our R&D engine

Trusted discovery data assets-

Molecular, reaction, assay, and process data are consistently available, documented, and reusable.

AI-ready scientific data-

High-quality, model-ready datasets accelerate analytics, machine learning, and AI initiatives.

Improved scientific decision-making-

Scientists can more easily access and interpret critical discovery information.

Connected discovery workflows-

Data from synthesis, purification, assay, and automation workflows are integrated and accessible.

Sustainable technical foundations-

Scalable solutions support long-term growth of discovery data and AI capabilities.

Qualifications

Required

• Master's degree or Ph.D. in Chemistry, Cheminformatics, Data Science, Computer Science, Pharmaceutical Sciences, Chemical Engineering, or a related scientific discipline.
• 5+ years of industry experience in pharmaceutical, biotechnology, or life sciences research environments.
• Strong understanding of small-molecule discovery workflows, including molecular structures, reaction data, synthesis workflows, and structure-activity relationships.
• Advanced proficiency in Python and SQL.
• Experience developing solutions on modern cloud data platforms, including Databricks and Snowflake.
• Significant experience working with molecular and reaction data using scientific software libraries and toolkits such as RDKit.
• Experience designing analytical workflows and data models for complex scientific datasets.
• Understanding of data engineering concepts including data modeling, metadata management, lineage, reproducibility, and data quality.
• Ability to collaborate effectively with scientists, engineers, and technology partners in a matrixed R&D environment.
• Strong communication skills and the ability to translate between scientific and technical audiences.

Preferred

• Experience supporting medicinal chemistry, synthesis, compound registration, or screening workflows.
• Familiarity with automated synthesis, laboratory automation, and high-throughput experimentation environments.
• Experience working with reaction informatics, reaction registration, or scientific workflow platforms.
• Experience with OpenEye scientific software.
• Experience developing machine learning solutions for molecular, reaction, or experimental datasets.
• Familiarity with FAIR data principles and scientific data governance practices.
• Experience working with graph-based, semantic, or ontology-driven approaches to scientific data integration.
• Knowledge of modern software engineering practices including testing, version control, CI/CD, and cloud-native development.

Why This Role Is Unique

This is an opportunity to shape how small-molecule discovery data enables the next generation of scientific research and AI-driven drug discovery. You will work at the intersection of experimental science, data science, and technology, helping transform diverse scientific data into connected, trustworthy, and reusable assets that accelerate discovery outcomes across Johnson & Johnson Innovative Medicine.

Ideal Candidate Profile

The ideal candidate combines strong data science capabilities with deep understanding of small-molecule discovery data and scientific workflows. They are equally comfortable discussing reaction data with medicinal chemists, designing scalable solutions with engineers, and developing analytical approaches that support discovery decisions. They are curious, collaborative, technically rigorous, and motivated by the opportunity to use data and AI to help bring better medicines to patients.

Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants’ needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers, internal employees contact AskGS to be directed to your accommodation resource.

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Required Skills:

Preferred Skills:

Advanced Analytics, Business Intelligence (BI), Coaching, Collaboration, Critical Thinking, Data Analysis, Database Management, Data Privacy Standards, Data Reporting, Data Savvy, Data Science, Data Visualization, Econometric Models, Process Improvements, Technical Credibility, Technologically Savvy, Workflow Analysis

The anticipated base pay range for this position is :

Additional Description for Pay Transparency:

Subject to the terms of their respective plans, employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).

This position is eligible to participate in the Company’s long-term incentive program.

Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:

Vacation –120 hours per calendar year

Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year

Holiday pay, including Floating Holidays –13 days per calendar year

Work, Personal and Family Time - up to 40 hours per calendar year

Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child

Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year

Caregiver Leave – 80 hours in a 52-week rolling period10 days

Volunteer Leave – 32 hours per calendar year

Military Spouse Time-Off – 80 hours per calendar year

For additional general information on Company benefits, please go to: - https://www.careers.jnj.com/employee-benefits