About Biocient
Biocient is a biotechnology company developing novel therapies for neurodegenerative diseases. Our research focuses on the role of mitochondrial dysfunction in disease biology and translating those insights into potential therapies that can alter disease progression and improve outcomes for patients.
About the Role
The Senior Data Scientist will own and continue building Biocient’s scientific data platform and analytics stack end to end — transforming raw experimental data into validated, decision-ready insights with the rigor, traceability, and reproducibility required to support drug development.
This is a highly hands-on role with broad ownership. As the dedicated data scientist at a fast-moving biotech, you will work across scientific data infrastructure, statistical analysis, computer vision, and internal AI tools. You’ll partner directly with scientists and leadership to build systems that make our experimental data more reliable, accessible, and actionable.
Key Responsibilities
- Own the scientific data platform. Manage and continue building AWS-based storage and data infrastructure for experimental data — tabular and imaging — including ingestion, structuring, quality control, backups, metadata, and user access across scientific and corporate workspaces.
- Own the internal AI assistant and knowledge base. Continue developing the in-house AI assistant used for tabular analysis, automated reporting, and image-based quantification, supported by controlled and reproducible analytical workflows. Maintain and expand the internal research knowledge base that serves as a trusted source of scientific information across the company.
- Own the image-analysis pipeline. Develop and maintain ML/computer-vision workflows for segmentation and quantitative analysis of microscopy and histology imaging; train or adapt models for new image and stain types; implement human-in-the-loop review; and cross-validate automated outputs against scientists’ manual analyses before rollout.
- Own data quality and validation. Build automated quality-control and error-flagging workflows, cross-validate internal findings against appropriate external datasets, and establish clear standards for assessing the reliability of internal and vendor-generated data.
- Analyze and interpret experimental data. Work directly with scientists to take behavioral, histological, imaging, and omics datasets from raw outputs through statistical analysis, visualization, interpretation, and decision-ready reporting.
- Partner with the ML Research Engineer. Deliver clean, model-ready datasets and own the data side of the prediction → experiment → result loop, helping connect computational outputs with experimental decisions.
Qualifications
Required:
- MS or PhD (preferred) in a quantitative field such as Statistics, Mathematics, Data Science, Engineering, or a related discipline.
- A minimum of 4 years of relevant industry experience building data platforms, analytical pipelines, and/or scientific analytics systems.
- Strong Python skills and experience building reproducible, production-quality analytical pipelines.
- Experience using AI coding assistants (e.g., Claude Code, Codex) to accelerate development of production-quality code.
- Experience working with version control, testing, documentation, and reproducible analytical workflows.
- Experience building LLM-based tools, assistants, or automations.
- Cloud data engineering experience, including AWS S3 and related services.
- Experience with ML/computer-vision approaches for image segmentation and quantitative image analysis.
- Strong applied statistics skills, including analysis of experimental data.
Strongly Preferred:
- Experience working with biological, translational, or preclinical research data.
- Experience in reproducibility-critical or regulated environments, including IND-supporting work.
- Experience with microscopy and/or histology imaging.
- Experience handling omics datasets such as proteomics, RNA-seq, or metabolomics.
Ideal Candidate
- Thrives with ownership and autonomy. Comfortable being the primary owner of a growing scientific data function and taking systems from concept through implementation, documentation, and ongoing improvement.
- Moves comfortably between engineering rigor and scientific judgment. Equally at home writing production-quality Python and assessing the statistical credibility of a small-cohort preclinical study.
- Computer-vision capable. Has hands-on experience building or operating ML-based image segmentation and quantitative image-analysis workflows, ideally for microscopy, histology, or other biomedical imaging.
- Communicates clearly and collaborates effectively. Works well with scientists, engineers, leadership, and other cross-functional partners and can translate analytical findings into clear decisions and next steps.
Compensation, Benefits & Perks
We offer highly competitive compensation package, commensurate with experience and qualifications. Additionally, this offer come with a competitive benefits package designed to support the health, well-being, and professional growth of our team, including:
· Medical, dental, and vision coverage
· HSA
· 401(k) with a company contribution equal to 3% of annual eligible compensation
· Generous paid time off
· 12 weeks of parental leave for eligible employees
· Training and professional development stipend
· Complimentary snacks, food, and beverages in the office
This is an onsite position based in our Torrance, CA office and is not available as a remote role.
Candidates must be currently authorized to work in the United States, as visa or green card sponsorship is not available for this position.
For candidates outside the Los Angeles area, relocation assistance may be available and can be discussed during the interview process.
Benefit eligibility and offerings may vary by position and are subject to the terms of the applicable plans and company policies.