Data Scientist

Culture Biosciences-posted 2 months ago

$141,000 - $195,000/Yr

Full-time • Entry Level

Hybrid • South San Francisco, CA

51-100 employees

Publishing Industries

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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.

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.

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.

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.

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

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