Senior Data Scientist - R&D DDSAI - Small Molecule Discovery

Description

The Data Science team in the company's Small Molecule Discovery organization is hiring a senior data scientist. The team works with medicinal chemists, automation scientists, data engineers, computational scientists and technology teams to turn discovery data into trusted, reusable, AI-ready assets.

You would combine discovery science, data science and scientific data engineering, helping decide how molecular, synthesis, purification and assay data are modeled and linked so they can support decisions, analytics, machine learning and AI across the discovery lifecycle.

Small-molecule discovery produces large volumes of complex, interconnected data across design, synthesis, purification, characterization and testing. Getting value from it means knowing how each workflow creates its data, how that data should be modeled and governed, and how to make it reusable for decision support, machine learning and AI-enabled discovery.

You would link scientific workflows to modern data platforms, helping discovery data deliver faster insight, better quality and support for AI work by partners in the In Silico Discovery group. The function is Data Analytics and Computational Sciences, within the Scientific/Technology job category.

Success means discovery data that is consistently available, documented and reusable; model-ready datasets; easier access to key discovery information; integrated synthesis, purification, assay and automation data; and scalable foundations for growing data and AI capabilities.

Responsibilities

• Design, build and maintain high-quality data assets for small-molecule discovery workflows.
• Turn molecular, synthesis, purification and assay data into reusable datasets for decisions and machine learning.
• Work with scientists and technology teams to set data requirements, business rules and analytical use cases.
• Build scalable analytical workflows on cloud data platforms and scientific computing tools.
• Apply data science methods to find insight in complex discovery data.
• Make sure scientific data is structured, documented and represented in a way that supports analytics and AI.
• Help define data standards, metadata practices and data quality frameworks for discovery data.
• Work with data engineering teams so data products stay scalable, traceable and reproducible.
• Prepare model-ready datasets for machine learning and scientific AI projects.
• Assess new ways to apply AI and advanced analytics within discovery workflows.
• Act as a trusted technical partner to medicinal chemists, automation scientists and in silico discovery teams.
• Convert scientific workflows and requirements into computational and data solutions.
• Contribute to best practice in scientific computing, data management and reproducible research.
• Mentor colleagues on modern data science methods and scientific data practices.
• Encourage collaboration across scientific, technical and data-focused teams.

Requirements

• Required: a master's or Ph.D. in chemistry, cheminformatics, data science, computer science, pharmaceutical sciences, chemical engineering or a related scientific field.
• Required: 5+ years of industry experience in pharmaceutical, biotechnology or life sciences research.
• Required: a solid grasp of small-molecule discovery workflows, including molecular structures, reaction data, synthesis and structure-activity relationships.
• Required: advanced Python and SQL skills.
• Required: experience building solutions on cloud data platforms such as Databricks and Snowflake.
• Required: substantial experience with molecular and reaction data using scientific libraries and toolkits such as RDKit.
• Required: experience designing analytical workflows and data models for complex scientific datasets.
• Required: working knowledge of data engineering concepts, including data modeling, metadata management, lineage, reproducibility and data quality.
• Required: ability to work effectively with scientists, engineers and technology partners in a matrixed R&D environment.
• Required: strong communication skills, able to translate between scientific and technical audiences.
• Preferred: experience supporting medicinal chemistry, synthesis, compound registration or screening workflows.
• Preferred: familiarity with automated synthesis, laboratory automation and high-throughput experimentation.
• Preferred: experience with reaction informatics, reaction registration or scientific workflow platforms.
• Preferred: experience with OpenEye scientific software.
• Preferred: experience developing machine learning solutions for molecular, reaction or experimental datasets.
• Preferred: familiarity with FAIR data principles and scientific data governance practices.
• Preferred: experience with graph-based, semantic or ontology-driven approaches to scientific data integration.
• Preferred: knowledge of modern software engineering practices, including testing, version control, CI/CD and cloud-native development.
• Preferred skills listed as: 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.

Conditions

Locations: Beerse and Antwerp (Belgium), Cornellà de Llobregat and Barcelona (Spain), Madrid (Spain), and Spring House, Pennsylvania (United States of America).

The company offers accommodations during the interview process on request.

Equal opportunity: the company values each person as an individual and respects diversity and merit.

Benefits

• Participation in the company's consolidated retirement plan (pension) and savings plan (401(k)), subject to plan terms.
• Eligibility for the long-term incentive program.
• Vacation of 120 hours per calendar year.
• Sick time of 40 hours per calendar year, or 48 hours per calendar year for Colorado residents and 56 hours per calendar year for Washington residents.
• Holiday pay, including floating holidays, of 13 days per calendar year.
• Work, personal and family time of up to 40 hours per calendar year.
• Parental leave of 480 hours within one year of the birth, adoption or foster care of a child.
• Bereavement leave of 240 hours for an immediate family member and 40 hours for an extended family member per calendar year.
• Caregiver leave of 80 hours in a 52-week rolling period and 10 days.
• Volunteer leave of 32 hours per calendar year.
• Military spouse time off of 80 hours per calendar year.
• Time-off eligibility depends on the terms of each policy and date of hire. More benefit details are on the company's benefits page.