Lead Scientist – Small Molecule Digital Chemistry Full-time

Lead Scientist – Small Molecule Digital Chemistry

Facility: Data & AI

Location: Lexington, MA, US

About the Department

In Silico Small Molecule & Cross Modality Discovery (ISCM) is dedicated to the research and development of small molecule, macrocycles and bioconjugate therapeutics. Our role is two-fold: support cutting-edge pharmaceutical research projects and develop innovative computational technologies in the digital chemistry field. To be successful, we foster strong collaborations with Small Molecule Medicinal Chemistry within our Therapeutics Discovery (TD) organization and colleagues across the Artificial Intelligence and Digital Innovation (ADI) organization. Our mission is to advance pharmaceutical projects through delivery of expert insights, in silico models and computational chemistry capabilities to enable in silico small molecule drug design and benefit patients across the globe.

We believe in the value of a diverse and inclusive culture. Together, we build and grow talent to ensure the development of novel solutions. The team is comprised of collaborative, diverse and passionate people who have a true sense of pride in their work. We are committed to helping each other grow, and we are driven by the opportunity to make a difference in the lives of people living with chronic disease. Everything we do starts and ends with the patient. And, while changing the future of chronic disease treatment, such as diabetes and obesity, is no easy task, we also recognize the importance of an enjoyable workplace, which is why we have cultivated a culture of fun, ingenuity, and innovation. Our competitive compensation package and support of a healthy work-life balance all add to a best-in-class employee experience.

The Position

The Lead/Principal Data Scientist – Small Molecule Digital Chemistry will contribute to the ISCM team's effort towards exploring, implementing, and applying computational chemistry and cheminformatics methods and tools to achieve DCD goals. The Lead/Principal Data Scientist will have knowledge and experience in advanced molecular modeling and computational drug design methods as well as small molecule project support. They will have a high degree of proficiency in modern 3D modeling tools for structure and ligand-based drug design, scientific programming, machine learning methods, and HPC/cloud computing. They will engage in drug discovery projects from early discovery to scale up and lead the development of complex workflows to prepare structural data, generate 2D/3D models, execute virtual screening, and perform small molecule design and optimization. The Lead/Principal Data Scientist will champion an in-silico first mindset and show initiative in recognizing and addressing unmet scientific needs using internal and external data.

***Please note we are open to hiring at Principal title commensurate with experience***

Relationships

The Lead Data Scientist – Small Molecule Digital Chemistry will contribute to the ISCM team's effort towards exploring, implementing, and applying computational chemistry and cheminformatics methods and tools to achieve the goals of Digital Chemistry and Design (DCD), our parent organization. The Lead Data Scientist will have knowledge and experience in advanced molecular modeling and computational drug design methods as well as small molecule project support. They will have a high degree of proficiency in modern 3D modeling tools for structure and ligand-based drug design, scientific programming, machine learning methods, and HPC/cloud computing. They will engage in drug discovery projects from early discovery to scale up and lead the development of complex workflows to prepare structural data, generate 2D/3D models, execute virtual screening, and perform small molecule design and optimization. The Lead Data Scientist will champion an in-silico first mindset and show initiative in recognizing and addressing unmet scientific needs using internal and external data.

Essential Functions

• Advance Small Molecule pharmaceutical project portfolio through computational chemistry method applications
• Develop digital chemistry processes and workflows to address pharmaceutical project needs.
• Provide pharmaceutical project teams with computational strategies to inform, influence, and prioritize designs for potency/selectivity and improve ADME/Tox endpoints
• Conceptualize approaches, identify capability gaps, and set goals within ISCM.
• Represent ISCM as a scientific lead on cross-functional teams that include discovery and research IT organizations
• Maintain a well-documented, reusable codebase, and traceable model history
• Maintain scientific and technical expertise through familiarity with scientific literature and attending conferences.
• Participate in the evaluation of external and internal capabilities and facilitate collaborations with external partners
• Present results to interdisciplinary teams of experimental, modeling scientists and machine learning colleagues

Physical Requirements

Up to 10% overnight travel may be required.

Qualifications

• Ph.D. with 6+ years of relevant experience required; M.Sc. with 8+ years can be considered. Degree in Computational Chemistry, Cheminformatics or related quantitative field preferred
• Relevant experience includes:
• Research experience in the field of small molecule drug discovery within industry or academia (industry preferred) as demonstrated by publications or presentations documenting impactful application of computational chemistry methods.
• Proficiency in general molecular modeling techniques (e.g. docking, molecular dynamics simulations, pharmacophore search, structure/ligand-based design).
• Hands on experience with molecular modeling software (e.g. Maestro, OpenEye, Rosetta, etc.) and cheminformatics packages (e.g. RDKit)
• Familiarity with QSAR/QSPR modeling, cheminformatics, and AI/ML methods.
• Proficiency in scripting or programming languages such as Python or C++
• Ability to perform in-depth data analysis and develop processes to solve complex problems
• Excellent written and oral communication skills, including presentation skills to diverse audiences
• Detail oriented with strong documentation skills
• Familiarity and working experience with a breadth of tasks of the Design-Make-Test-Analyze drug discovery cycle – highly preferred