# Scientist II, Developability at Bighatbiosciences

> Onsite · United States · Mid-level · Other · open. Source: https://alderhq.app/jobs/pinpoint%3Abighatbiosciences%3A526442 (read 2026-11-15).

## Facts (observed)

- Company: [Bighatbiosciences](https://alderhq.app/companies/bighatbiosciences)
- Location text: San Mateo, CA, CA
- Where it can be done from (inferred): Onsite · United States (evidence: "Location: San Mateo, CA, CA")
- Posted: already open when tracking began; date unknown
- First seen by alder: 2026-11-04 · last verified: 2026-11-09
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://bighatbiosciences.pinpointhq.com/en/postings/da57d3d6-24a9-4df8-857e-2e0fb6ce2205

## Pay and sponsorship

- Posted pay: $145k–$165k per year (from the description)
- Market band for similar posted roles (SF Bay Area, n 113): p25 $104k, median $168k, p75 $225k

## Description (the employer's text)

The Role: BigHat Biosciences is looking for a hands-on, bench-driven scientist to drive antibody developability assessments that advance our Milliner Platform for AI-designed therapeutics. This is a primarily lab-based role where you'll spend the majority of your time at the bench executing and innovating on our developability workflows.

\*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.

### Responsibilities

- Lead developability R&D projects: design, optimize, and execute high throughput developability assays to expand BigHat’s toolkit.
- Drive developability assessments (purity, stability, tolerability, biophysical properties) across programs, with strong attention to data interpretation and organization.
- Support late-stage characterization and IND-enabling studies, including formulation screening, stress testing, peptide mapping, and simulated administration studies, to rank and advance lead candidates.
- Serve as the Developability lead within project teams, guiding experimental strategy to address liabilities and hit program milestones.
- Work cross-functionally to automate and train colleagues on new and existing methods, build QC frameworks for monitoring assay performance, and adapt workflows to existing LIMS infrastructure.
- Proactively and independently analyze data, interpret scientific findings, propose next steps, and broadcast findings clearly across the organization.
### Skills

- PhD in Biochemistry or relevant discipline with 3+ year(s) of industry experience; exceptional non-PhD candidates with deep bench experience will be considered.
- Strong background in biophysical and analytical characterization of antibodies and antibody fragments: SEC, HIC, CE-SDS, DLS, DSF, ELISA, LC-MS, including method development and optimization.
- Track record of translating complex data into clear results and recommended actions.
- Experience with protein structures and antibody engineering.
- Enthusiastic about learning and onboarding new technologies to expand capabilities and improve work quality, timelines, throughput or cost.
- Nice-to-haves include prior experience working in a dynamic start-up environment, working as a project lead, and working with automation.
### Benefits

The salary estimated for this position is $145,000 - $165,000 + 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

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/pinpoint%3Abighatbiosciences%3A526442 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.