Associate Scientist, Display Technologies

The role

BigHat Biosciences is seeking a curious and motivated Associate Scientist to join the Display Technologies team. This individual will contribute to BigHat’s antibody discovery and engineering efforts and help generate high-quality data to improve BigHat’s machine learning models using display technologies, working closely with senior scientists and cross-functional teams.

At BigHat we believe in titles that commensurate with skill set, relative organizational impact, and value contribution; more experienced candidates are encouraged to apply, with the understanding that responsibilities and title would adjust as appropriate.

Key Responsibilities

• Support R&D projects advancing display technologies at BigHat that expands BigHat's antibody discovery capabilities and feed its ML models.
• Lead in the construction and QC of phage and yeast display libraries across diverse antibody formats (VHH, scFv, Fab) using standard molecular biology techniques (PCR, molecular cloning, electroporation).
• Execute phage and yeast display selections using naive and affinity and stability maturation libraries to discover and engineer antibodies with desired therapeutic properties.
• Express, purify, and characterize display-derived molecules using assays including ELISA, flow cytometry, BLI/SPR, CE-SDS, and others.
• Analyze selection results and contribute to discussions on next steps and future experimental design.
• Collaborate with BigHat’s Data Science and Machine Learning teams to inform library design and interpret selection data for model training.
• Present experimental plans and results during regular meetings with manager and science teams.
• Maintain thorough records using LIMS and electronic notebooks.

Skills Knowledge and Expertise

• BS or MS in Biochemistry, Molecular Biology, Bioengineering, or a related field.
• 4+ years of hands-on laboratory experience (academic or industry); relevant internship or research experience welcome.
• Familiarity with general molecular biology techniques (PCR, molecular cloning, gel electrophoresis).
• Exposure to antibody biology, display technologies (phage or yeast), and protein expression.
• Demonstrated ability to follow protocols carefully, troubleshoot experiments, and maintain detailed lab records.
• Effective time management and clear written and verbal communication skills.
• Collaborative, team-oriented mindset with an eagerness to learn in a fast-paced startup environment.
• Nice-to-haves include experience with flow cytometry, ELISA, or other binding assays, and familiarity with NGS or automation platforms.

Total Rewards

The salary estimated for this position is $120,000 - $135,000 + bonus + options + benefits. Compensation will vary depending on job-related knowledge, skills, and experience. Actual compensation will be confirmed in writing at the time of the offer.

What BigHat Offers:

• Range of health insurance plan options through Anthem and Kaiser (monthly credit if benefit waived)
• Dental, and vision coverage through Guardian
• Additional well-being benefits through Nayya, OneMedical, Wagmo, Rula, and more
• 401(k) with company match
• DTO, two weeks of company-wide shutdown, and 12 company holidays
• Paid parental leave

About BigHat Biosciences

BigHat Biosciences designs safer, more effective biologic therapies for patients using machine learning and synthetic biology.

BigHat integrates a wet lab for high-speed characterization with machine learning technologies to guide the search for better antibodies. We apply these design capabilities to develop new generations of safer and more effective treatments for patients suffering from today’s most challenging diseases.

BigHat is a Series B biotech outside San Francisco with a team-oriented, inclusive, and family-friendly culture. Our broad pipeline of wholly-owned and partnered therapeutic programs span many disparate indications with high unmet need, such as cancer, inflammation, and infectious disease. BigHat has raised >$100M from top investors, including Section 32, a16z, and 8VC.

Our Hiring Process

Stage 8:
Offer (Pending References)
Stage 9:
References
Stage 10:
Hired
Stage 1:
Applied
Stage 2:
Initial Recruiter Screen
Stage 3:
Initial Conversation | Head of Talent
Stage 4:
Initial Conversation | Hiring Manager
Stage 5:
1st Technical Screen
Stage 6:
2nd Technical Screen
Stage 7:
Full Panel Interview
Stage 8:
Offer (Pending References)
Stage 9:
References
Stage 10:
Hired
Stage 1:
Applied
Stage 2:
Initial Recruiter Screen
Stage 3:
Initial Conversation | Head of Talent
Stage 4:
Initial Conversation | Hiring Manager
Stage 5:
1st Technical Screen
Stage 6:
2nd Technical Screen
Stage 7:
Full Panel Interview
Stage 8:
Offer (Pending References)
Stage 9:
References
Stage 10:
Hired