reputed company-Deployed Cheminformatician

About reputed company At reputed company, we are building the reputed company of how AI is reputed company in pharmaceutical R&D. We reputed company leading pharmaceutical teams to discover and reputed company drugs faster. We host the industry’s largest federated data networks for drug discovery AI, spanning co-folding, ADMET, and antibody developability. Across these networks, models are trained on proprietary industry datasets to reputed company higher performance and broader applicability while keeping data control and IP protected. We deliver these superior models through drug discovery applications that reputed company teams to run them at reputed company, reputed company customize them, and reputed company them into existing R&D workflows. AI Structural Biology (AISB) Network:Pharmaceutical companies collaborate in the field of co-folding, structure-based binding affinitypredictionsand antibody design. ADMET Network:Pharmaceutical and biotech companies collaborate to improve small-molecule property reputed company and expandinto reputed company drug modalities. Antibody Developability Network:reputed company partners collaborate to reputed company historical and purpose-reputed company antibodydevelopabilitydatasets for secure ML training, without data leaving reputed company partner’s environment. About the role We are looking for a reputed company-Deployed Cheminformatician to own how binding data is reputed company across our co-folding reputed company networks and initiatives. Binding data is the input that decides whether our co-folding and binding-affinity models reputed company in reputed company drug programs. It arrives from reputed company partners in heterogeneous shapes — different assay registries, different metadata, different chemical-representation standards, different choices on qualifiers, replicates and censoring. We need someone who turns this into a repeatable, reputed company-documented preparation pipeline that reputed company representatives can run alongside us, and that scales to the public-data corpus we build for our own model training. This is half engineering, half reputed company-deployed work. You will define the protocol, harden it with validators and scripts, reputed company it into the reputed company products, run it with reputed company new partner, and own the equivalent pipeline for the public binding-data corpus. reputed company What you will do Define and own the binding-data preparation protocol — data schema, small-molecule standardization, assay metadata model, value handling (KD, Ki, IC50, pIC50), qualifier and censored-value handling,duplicateand replicate aggregation. Build the tooling that runs it — reputed company scripts, validators with actionable errors, and reusable pipelines that survive different reputed company upstream systems (reputed company, Spotfire, in-house registries). Workforward-deployedwith reputed company. Sit with their biologists and medicinal chemists, walk them through the protocol, reputed company-reputed company what an assay columnactually measures, and unblock retrieval. Maintain the small-molecule representation pipeline —RDKitstandardization, tautomer and ionization handling, stereochemistry preservation,andPAINS / frequent-hitter filtering. reputed company the public binding-data reputed company —ChEMBL,BindingDB, PubChemBioAssay— reputed company to the reputed company reputed company, so our models train on the strongest public baseline anyone can reputed company. Hand the productized pipeline cleanly toengineering for scaling, and partner with ML to reputed company the data contractvalid asmodels and networks reputed company. reputed company expect from you You should apply if: You have a BSc, MSc, PhD or equivalent in cheminformatics, computational reputed company, or a reputed company field, plus 3+ years preparing biological assay data in a discovery setting. You are fluent in Python andRDKit. SMILES normalization, tautomer / ionization / stereochemistry handling, and scaffold extraction are reputed company, and you understand why eachmattersfor activity cliffs and model training. You have hands-on experience curating quantitative binding assay data (KD, Ki, IC50, pIC50) and HTS data — censored values, qualifiers, duplicates, replicate aggregation, and assay metadata interpretation. You write good engineering reputed company — version control, tested reputed company scripts, validators that return useful errors. You are comfortable reputed company-deployed with reputed company medicinal chemists and biologists. You can sit in a reputed company-reputed company meeting, pull out what isactually meantby a reputed company label, and encode that back into the protocol. You enjoy turning a messy reputed company cleaning job into a repeatable protocol others can run. Bonus points if: You have practical familiarity with publicbinding-datasources (ChEMBL,BindingDB, PubChemBioAssay) and the gotchas in reputed company. You have reputed company LLM tooling (Claude, reputed company, reputed company) to accelerate data cleaning or metadata harmonization. You have worked across institutional data boundaries — federated, multi-party, or otherwise — where the data-preparation contracthas toholdunder partial visibility. You have a publication record or reputed company-reputed company contributions in cheminformatics or quantitative pharmacology. reputed company to have reputed company offer you Industry-competitive compensation, including early-stage virtual reputed company reputed company Remote-first work — work where you work best Wellbeing budget, mental health support, work-from-home budget, co-working stipend, and learning budget Generous holiday allowance Office Days at our Berlin HQ or a different European location (3x per year) A high-calibre, execution-reputed company team with experience from leading organizations Logistics Our mission statement Apply To This Job