Compared with the selected benchmark ("All roles in Berlin, Germany"), this listing's salary midpoint is about 94% lower. The offer sits below the benchmark range (€1,667–€21,083). The listed pay band (€650–€685) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 10 comparable listings.

Monthly salary comparison for Forward-Deployed Scientist
Market	Lower bound (25th percentile)	Median	Upper bound (75th percentile)
All roles in Berlin, Germany	€1,667/per month	€8,010/per month	€21,083/per month

About the role

What we offer you - Industry-competitive compensation, including early-stage virtual share options - Remote-first working – work where you work best, whether from home or a co-working space near you - Great suite of benefits, including a wellbeing budget, mental health benefits, a work-from-home budget, a co-working stipend and a learning and development budget - Regular team lunches and social events - Generous holiday allowance - Office Days at our Berlin HQ or a different European location (3x a year) - A fun, diverse team of mission-driven individuals with a drive to see AI and ML used for good - Plenty of room to grow personally and professionally and shape your own role

Job Details

Responsibilities

Act as a forward-deployed scientist, focused on driving adoption and real, measurable impact
Work hands-on with pharma users of the Co-Folding Application, guiding benchmarking, testing, and application to real discovery programs
Build relationships with the relevant stakeholders across pharma R&D, from computational and medicinal chemists to program leaders
Feed insights from the field back to Product and the AI Applications Team to shape platform improvements
Run in-person and remote workshops to train users and share best practices with research teams
Develop case studies that demonstrate impact and can be replicated across projects
Contribute scientific content such as example datasets, usage guidelines, and evaluation protocols

Requirements

PhD in computational chemistry, medicinal chemistry, or a related field
Hands-on experience as a power user in structure-based workflows - co-folding, docking, protein–ligand modeling in real drug discovery programs
Familiarity with molecular visualization and cheminformatics tools (e.g., PyMOL, RDKit)
Credibility with both computational and medicinal chemists, and ability to bridge what each group needs
Basic scripting skills to run and explain notebooks and analyses
Comfortable working without full specifications - takes ownership, makes progress under ambiguity
Communicates clearly across technical and non-technical audiences