Customer Data Scientist (Industrial Biotechnology)

Das ist der Job

Role Description We’re looking for a Customer Data Scientist to ensure customer programs run smoothly and reliably .

Darum lohnt es sich

You’ll work closely with the lab team and the customer-facing technical lead to run production analyses, maintain lab data pipelines, and generate reports/datasets using existing methods and tools.

How You’ll Work You’ll receive well-scoped work packages from a technical lead You’ll execute analyses in collaboration with our wet lab and dry lab teams and deliver results independently You’ll flag data quality issues, edge cases, and inconsistencies early Over time, you’ll help turn one-off analyses into standardized workflows Key responsibilities Customer & Lab Data Execution Process incoming laboratory data from customer and internal experiments Run production-ready analysis pipelines and algorithms on new datasets Generate structured outputs for downstream integration into our software platform Work with the lab team to ensure data completeness, correctness, and traceability Data Pipelines & Quality Control Maintain and extend lab data processing pipelines Build and monitor QC checks, validation steps, and basic anomaly detection Create dashboards and summary views to track data health and experiment status Improve robustness and reproducibility of data flows over time Reporting & Analysis Create customer-facing analytical reports (e.g. multi-strain comparisons, growth summaries) Standardize recurring analyses into reusable scripts or pipelines Support design-of-experiments (DOE) analyses for new lab iterations Clearly document assumptions, inputs, and outputs for each analysis Help move research or prototype scripts into stable, production-ready code Refactor and package commonly used analyses for reuse Contribute to internal documentation, runbooks, and templates Collaborate with software engineers to ensure clean handoff of results Growth Outlook As the company grows, this role can expand toward: Ownership of larger portions of the data pipeline Mentoring junior analysts or interns Leading standardization efforts across customer programs Qualifications Bachelor’s or Master’s degree in data science, bioengineering, computational biology, statistics, or a related field 1–3 years of experience working with real-world scientific or laboratory data Strong Python skills (data processing, analysis, scripting) Experience working with structured datasets (tables, metadata, experimental results) Comfort running existing analyses and following established pipelines Clear written communication and documentation habits Nice-to-have Experience with lab data, biological experiments, or industrial biotech.

Familiarity with QC, validation, or monitoring of data pipelines Exposure to DOE or experimental design Experience collaborating with software or platform teams Experience with computational biology or data-driven methods (classical machine learning, deep learning, or LLMs) Get on board early: Become an early part of a visionary team that is leveraging the power of digital biology to unlock the $4tn bioeconomy; Competitive compensation through salary + stock options; we are looking to build a small but mighty team and think about compensation along those lines; Leadership opportunity: Work closely with visionary founders and grow into a leadership role with significant responsibility; A beautiful office in the heart of Munich #J-18808-Ljbffr You will turn raw experimental data into clean, production-ready analytics that directly power our platform and customer deliverables.

This role is crucial because it’s the quality gate and execution engine between the lab and production systems: if data is processed correctly and consistently, insights ship, reports stay dependable, and our software gets better with every dataset. This role is focused on execution and reliability .

In particular, how to deal with the often messy or unstructured assets that already exist in organizations.