Lead In Silico Business Partner, Platform

Job Title: Lead In Silico Business Partner, Platform

Job Type: Permanent

Location: Abingdon - UK, Alderley Park- UK or Verona, Italy

Our Company

Evotec is a leader in the discovery and development of novel small molecule drugs with operational sites in Europe and the US. The Company has built substantial drug discovery expertise and an industrialised platform that can drive new innovative small molecule compounds into the clinic. In addition, Evotec has built a deep internal knowledge base in the treatment of diseases related to neuroscience, pain, oncology, inflammation and metabolic diseases. Leveraging these skills and expertise the Company intends to develop best-in-class differentiated therapeutics and deliver superior science-driven discovery alliances with pharmaceutical and biotechnology companies

Purpose of the role

• The Lead In Silico Business Partner, Platform is the single front door between Evotec’s Drug Discovery Platforms (DDP) segment and the global In Silico & AI organization, owning the relationship, the demand and the in silico roadmap for the segment worldwide.

• The role translates platform science priorities across DMPK, ADME/Tox, predictive and in vitro safety, hit identification and screening, biophysical and structural methods, bioanalysis, sample and reagent management and omics data generation into prioritized in silico and AI requirements, then orchestrates delivery across the capability units and holds it to quality, timing and measurable value.

• This is one of four Lead Business Partner seats in the newly established Strategy & Portfolio unit. It carries a commercial mandate alongside the scientific one: ADMET/Safety is one of three capabilities Evotec is industrializing as a differentiator, and this is the role that makes it land in the platform business.

Core accountabilities

• Own the end to end relationship between the Drug Discovery Platforms segment and the In Silico & AI function globally, acting as the single accountable front door for all incoming demand so that work is scoped and staffed once, not duplicated across teams.

• Shape and own the in silico and AI roadmap for the platform business, with particular focus on ADMET/Safety and in vitro predictive safety (NAMs) as well as omics data generation, one of the three capabilities Evotec is industrializing as a differentiator.

• Capture, structure and prioritize demand from platform leadership, translating scientific and operational needs into clear, testable requirements together with Solution Managers, the AI Accelerator and Solutions & Data.

• Orchestrate the in silico contribution across Bioinformatics, Computational Biology, Therapeutics Design, AI Accelerator and Solutions & Data, ensuring alignment, delivery quality and timely execution.

• Partner with the omics data generation platforms to turn generated data into governed, reusable data assets that compound across projects, in close collaboration with IT&Data.

• Drive adoption at scale, moving in silico and AI capability out of pilot and into routine platform operation in place of repeated proofs of concept.

• Provide structured input to segment and portfolio level prioritization, including demand visibility, cross unit dependencies, resourcing needs, investment cases and expected value.

• Contribute the in silico content to client proposals and bids where platform services are in scope, working with Commercial, Business Development and Global Portfolio Management on differentiation and pricing.

• Track and evidence the value delivered, including margin uplift on in silico influenced work, cycle time and de-risking impact, and in silico attributed revenue, feeding this back into prioritization.

• Serve as moderator and escalation point for conflicting priorities, with support from the In Silico function heads.

• Represent In Silico & AI in platform leadership forums and act as a change agent for new ways of working across a global, multi site organization.

Capability, Knowledge and Experience:

• Proven ability to build trusted relationships with senior scientific and operational leadership, and to influence without direct authority in a global matrix

• Working technical fluency in the in silico toolbox that platform science depends on: machine learning and QSAR based property and ADMET prediction, cheminformatics, structure based and biophysical methods, PBPK and PK/PD modelling, and multi omics analysis. Depth in several, credible literacy across all

• Practical understanding of the AI delivery lifecycle, including data quality and FAIR principles, model validation, MLOps, and what it takes to move a model from prototype i