Research Scientist (all genders) Discovery Data integration

• Enable data-driven early discovery by integrating and translating multimodal biological datasets into actionable insights that strengthen target validation and decision quality.

• Integrate, harmonize, and curate complex datasets across targeted assays, imaging, RNA-seq/single-cell, CRISPR screens, proteomics, and genomics.

• Partner with Early Discovery and Target Validation teams to shape study design, align analytical strategies, and interpret results in a biological context.

• Translate complex data into clear, decision-relevant biological insights to support go/no-go and portfolio prioritization decisions.

• Operationalize fit-for-purpose statistical and analytical approaches, working closely with bioinformatics and data science experts.

• Deliver high-impact insight products (e.g. visual analytics, concise target insight reports) that enable transparent communication of findings.

• Establish and continuously improve data collection, metadata, and governance standards to ensure compliant, traceable, and reusable target validation data.

• Embed Design of Experiments (DoE) and Quality by Design (QbD) principles within laboratory and discovery workflows.

• Build scalable, automation-ready data processes that maximize the value of perturbation and assay data across Evotec’s discovery portfolio., * A position within a vigorous and exciting professional environment promoted by an open culture and a spirit of community
• A diverse, international workforce with a dynamic working environment that fosters creativity, innovations and teamwork
• 30 days of annual holiday, flexible working hours, and in-house canteen
• Capital forming benefits, holiday allowance, annual bonus depending on performance, and monthly allowance for public transportation (Deutschlandticket - JobTicket Premium)

• Ph.D. in Cell Biology, Molecular Biology, or a related field with proven experience in Computational Biology, Bioinformatics, or Systems Biology approaches supporting data-driven decisions; or equivalent professional experience.

• 3-6+ years’ experience integrating, analyzing, and interpreting multimodal biological data in discovery settings (targeted assays, imaging/cell painting, transcriptomics incl. single-cell, CRISPR screens, proteomics, genomics).

• Demonstrated expertise in statistics, DoE, and QbD for in-vitro assays to ensure robust experimental design and decision-making.

• Proficiency in R and strong data visualization skills.

• Proven collaboration and communication skills working across cross-functional science and data teams.

• Familiarity with target validation and perturbation experimental approaches and laboratory processes.

Further ideal qualifications

• Experience with workflow/insight app automation (e.g., Shiny, Dash, Power BI) to scale analytics.

• Exposure to laboratory automation to streamline data capture and quality.