Data Scientist

About Us:

Culture’s mission is to simplify and accelerate bioprocess development to enable our customers to bring their biopharmaceutical products to market faster.

With a focus on upstream cell culture process development, Culture has developed a unique platform that merges products, services and data management that can be applied to mammalian, microbial and viral vector production processes. This platform enables high-throughput process development projects to be rapidly and seamlessly executed directly by our customers in their own facilities, in our service laboratories, or both, all driven by our cloud-connected web application, accessible from anywhere, for designing, managing and analyzing experiments.

At Culture, we combine our passions for biomanufacturing, engineering, and operations to accelerate the future of biomanufacturing with cutting-edge tools for experimentation, optimization, and AI-driven decision-making. We value collaboration for exceptional results, innovate with purpose, and earn our customers’ trust every day.

The Opportunity: 

We are seeking a Data Scientist who is passionate about solving complex problems at the intersection of data science, bioprocessing, software and automation. You will collaborate with product, engineering, and scientific teams to design and develop advanced analytics solutions that help optimize upstream and downstream processes, improve product quality, support decision-making, and accelerate end-to-end biopharma process development timelines. This role is ideal for someone who thrives on turning complex experimental data into actionable insights, scalable pipelines, and production-ready models.

What you'll do:

• Partner with product leadership to shape and execute our advanced analytics strategy and roadmap.
• Collaborate with bioprocess scientists, engineers, and customers to deeply understand experimental workflows and data challenges.
• Perform rigorous exploratory data analysis (EDA) on large-scale, multi-modal, and time-series datasets to uncover novel insights that guide process development strategies.
• Build, optimize, and maintain scalable data pipelines for cleaning, transforming, and feature engineering raw bioprocess data, ensuring quality and reproducibility.
• Design, develop, and validate statistical and machine learning models, and integrate them into customer-facing software platforms.
• Work cross-functionally with Process Engineers, Software Developers, and Automation Specialists to translate scientific hypotheses and business needs into impactful, production-ready data science solutions.
• Effectively communicate complex findings to both technical and non-technical stakeholders through compelling visualizations, reports, and presentations.
• Stay current with advancements in machine learning, biostatistics, and bioprocess engineering, applying them to continuously strengthen our platform’s analytical capabilities.

Basic Qualifications:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Bioinformatics, or a related field.
• 2+ years of experience applying data science or machine learning in a biotech, pharmaceutical, or bioprocessing environment.
• Proficiency in SQL, Python, and experience with data science libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas, NumPy).
• Strong knowledge of data modeling, data warehousing, and ETL processes.
• Demonstrated ability to translate complex data into actionable scientific insights with statistical rigor.
• Strong communication skills, with the ability to explain complex technical concepts clearly to a diverse group of stakeholders.

Nice-to-have:

• Comfortable with cloud computing platforms (AWS, GCP, Azure) and big data frameworks (Spark, Databricks).
• Familiarity with laboratory or pilot-scale bioprocess equipment (e.g., bioreactors, fermenters, or cell culture systems), or strong interest in learning.
• Experience with time-series data analysis and ODE/differential equation modeling.
• Knowledge of numerical optimization methods (gradient descent, Newton's methods, Bayesian optimization).
• Experience with Design of Experiments (DoE) methodologies and tooling.
• Comfortable with development best practices such as CI/CD and MLOps.
• Proven ability to take a thoughtful, pragmatic, and efficient approach to problem solving.
• Passionate about up-leveling yourself and those around you through curiosity, mentorship, and fostering a collaborative and inclusive team environment.

Location & Schedule:

• This is a hybrid position. We’re looking for someone based in the San Francisco Bay Area who is able to work in person at our office in South San Francisco at least 3 days per week.

Base Salary Range:

Culture Biosciences's compensation package includes market competitive salary, equity for all full time roles, and great benefits. Our expected salary range for this role is $141,000-$195,000. We are hiring for multiple levels and backgrounds so final offers may vary within the range provided based on experience, expertise, and other factors.

Benefits:

• Competitive salary and equity compensation
• Medical, Dental, Vision, and Life insurance
• Medical and Dependent Care FSA (prorated based on start-date)
• 401(k) plan with company match
• Responsible Time Off (non-accrual based) policy, 11 paid company holidays and a week-long winter break
• 12 weeks of parental leave at full salary

Culture Biosciences provides equal employment opportunities to all employees and applicants. We seek to build a company that promotes inclusion and expands the diversity of our industry as a whole. We encourage people with identities underrepresented in biotech and technology to apply.