R&D Cheminformatics Data Scientist

Today, Lonza is a global leader in life sciences operating across three continents. While we work in science, there’s no magic formula to how we do it. Our greatest scientific solution is talented people working together, devising ideas that help businesses to help people. In exchange, we let our people own their careers. Their ideas, big and small, genuinely improve the world. And that’s the kind of work we want to be part of.

Lonza is seeking an experienced and motivated Cheminformatics Data Scientist to join the Small Molecules R&D team. They will broaden and deepen the Division’s capabilities in the development and application of R&D cheminformatics, with a focus on Preclinical CMC workflows. This role is integral to R&D’s mission to develop innovative technology platforms that accelerate the clinical readiness of our clients’ groundbreaking therapeutics.

Our new colleague will be responsible for developing innovations in a broad range of cheminformatics areas, including – as non-limiting examples – complex molecule synthesis, reaction and process optimization, automation integration, and HTE experimentation and large scale data analysis.

*This position is fully remote*

Key Responsibilities:

• Leverages data search, retrieval, and modelling to accelerate CMC workflows, working collaboratively with Drug Substance (DS) and Drug Product (DP) R&D and Operations colleagues.
• Collaborates with technical and commercial stakeholders to uncover, validate, and prioritize areas for innovation in cheminformatics and data science
• Integrates information from a variety of disciplines (chemical synthesis and manufacturing; pharmaceutical sciences, opportunistically) and sources (technical and commercial) to uncover actionable insights and new Lonza IP.
• Leads technical and commercial stakeholders to data-driven decisions on the selection and internal use of state-of-the-art cheminformatics technologies, including augmentation of off-the-shelf cheminformatics solutions
• Develops methods and capabilities for archiving and retrieving data on molecular structures, reaction pathways, molecular interactions, and other pharmaceutically relevant phenomena.
• Identifies chemical property classifications and trends from large databases using mathematical and cheminformatics techniques.
• Trains and advises DS and DP R&D and Operations colleagues about the cheminformatics capabilities available to them – those newly developed in R&D and pre-existing.
• Promotes the benefits of Small Molecules’ cheminformatics and data science advances through publications (patents, peer-reviewed journal articles, technical marketing communications) and public speaking engagements (conference presentations, poster sessions, roundtables, etc.)

Key Requirements:

• PhD in Organic Chemistry, Cheminformatics, Computational Chemistry, or related scientific field with significant experience within pharmaceutical, fine chemicals, or biotechnology field. -OR-MS/MA in Organic Chemistry andMS Cheminformatics or MS Computational Science with significant years of experience within pharmaceutical, fine chemicals, or biotechnology field. Candidates with combined experience in laboratory research settings (organic synthesis or method development) and cheminformatics or data science are strongly encouraged to apply.
• Demonstrated cheminformatics expertise in areas such as applied AI and machine learning, chemical reaction/library enumeration, 2D/3D similarity, clustering, text-mining, dimensionality reduction techniques pertinent to data mining and data visualizations – with proven track record of accomplishments
• Strong fluency in at least one scientific scripting or programming language (e.g., R or Python) and at least one querying language (e.g., SQL)
• Proficiency with cheminformatics pipelining tools (e.g., KNIME) and leveraging toolkits, therein (e.g., RDKit, CDK, Erlwood, etc.) and libraries (e.g., TensorFlow, PyTorch, DeepChem)
• Demonstrated understanding of critical assessment of molecule-property data, reaction process data, and predictive model quality.
• Passion: You love to draw unique insights in organic synthesis, process chemistry, and material science through the combination, normalization, and analysis of disparate data
• Entrepreneurial mindset: You thrive on defining key challenges, innovative solutions, andthe commercial benefits of research investments, to grow the company and team
• Great communication and presentations skills: You enjoy telling stories with data, internally and externally.
• Roll-up-your-sleeves Leadership: You are happy to teach by demonstration as needed, and to individually contribute to achieve project success.

Every day, Lonza’s products and services have a positive impact on millions of people. For us, this is not only a great privilege, but also a great responsibility. How we achieve our business results is just as important as the achievements themselves. At Lonza, we respect and protect our people and our environment. Any success we achieve is no success at all if not achieved ethically.

People come to Lonza for the challenge and creativity of solving complex problems and developing new ideas in life sciences. In return, we offer the satisfaction that comes with improving lives all around the world. The satisfaction that comes with making a meaningful difference.

Lonza is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, status as a qualified individual with disability, protected veteran status, or any other characteristic protected by law.