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Senior Scientist, High-Throughput Protein Binder Screening

Digital Biology

Watertown, MAFull-timePosted 2w agoStill listed 1 day ago

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At a glance

Compensation
No compensation found
Location
Watertown, MA
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

Digital Biology is hiring a Senior Scientist to lead its partnered high-throughput protein binder screening operation. The role combines hands-on workflow optimization with leadership of research associates, overseeing work from DNA library construction through analysis and quality control. The scientist will establish standardized protocols, train teams, collaborate with computational scientists, and work with partners to define data goals and deliver quality data.

Skills & qualifications

RequiredNice to have

Skills

Protein EngineeringMolecular CloningHigh Throughput ScreeningData AnalysisQuality ControlTeam ManagementHigh-Throughput AssaysDNA Library ConstructionDisplay CampaignsNGS Library PreparationSequencing-Based AnalysisSOP WritingWorkflow StandardizationTeam TrainingAutomated Liquid Handling

Qualifications

5+ Years Industry ExperiencePhD in Molecular Biology, Protein Biochemistry, or Related Field

Benefits

Medical Insurance
Vision Insurance
Dental Insurance
401(k) Match

Full job description

Senior Scientist, High-Throughput Protein Binder Screening Location: Watertown, MA Employment Type: Full-time, on-site Reports to: CSO Direct reports: Research Associates, High-Throughput Protein Binder Screening About Digital Biology Digital Biology is the data lab for AI protein drug engineering, building a measurement-driven discovery engine for next-generation biologics. We combine high-throughput experimental systems, advanced molecular technologies, automation, and computational modeling to generate biological data at unprecedented scale and resolution. Our team works across protein engineering, functional screening, spatial biology, and AI-guided drug discovery. We partner with leading biotechnology and pharmaceutical organizations to build training and validation datasets that enable the design of better therapeutic proteins. The Position Digital Biology is hiring a Senior Scientist to lead our partnered high-throughput protein binder screening operation. We are looking for an expert in protein library methods and molecular cloning who champions process: standardized protocols, robust SOPs, and well-trained teams. You will also stay hands-on, optimizing protocols and supporting successful operation of the workflow end to end, from library construction through analysis and QC. In this role, you will have the opportunity to grow a team screening millions of proteins per month, and to interface directly with our partners in defining data goals and delivering quality data. Responsibilities

  • Lead research associates running high-throughput screening campaigns at a scale of millions of proteins per month.
  • Own the core workflow end to end: DNA library cloning, production, selection, NGS preparation, analysis, and QC.
  • Establish SOPs, standardized protocols, and training materials.
  • Optimize protocols hands-on to improve robustness, throughput, cost, and turnaround, leveraging lab automation to scale and maintain consistency.
  • Set QC metrics and acceptance criteria, and sign off on data.
  • Work closely with computational scientists to close the loop, reporting progress and risks to the team and partners.

Qualifications

  • 5+ years of industry experience running high-throughput assays; PhD in molecular biology, protein biochemistry, or a related field preferred
  • Expert in molecular cloning, with hands-on experience building DNA libraries
  • Experience running display campaigns (e.g. phage, yeast, mammalian)
  • Working knowledge of NGS library preparation and sequencing-based analysis and QC
  • A track record of writing SOPs, standardizing workflows, and training teams to run them reliably
  • Experience managing research associates or scientists; automated liquid handling a plus

What We Offer

  • The ability to generate and validate protein binding data at scale on one of the most capable experimental screening platforms
  • A chance to shape the data foundations behind AI-driven protein and antibody design
  • Close collaboration with experts in protein engineering, laboratory automation, and computational biology
  • An ambitious team solving hard problems at the intersection of hard tech, biology, and ML.
  • Highly competitive salary, equity, and benefits package

Digital Biology is an equal-opportunity employer. We value different experiences, perspectives, and ways of thinking, and we believe the strongest scientific teams are built by bringing together people with diverse backgrounds and expertise.

Company Benefits: Health, vision, life, dental insurance and 401K plan. If you don't meet all of the requirements listed here, we still encourage you to apply or reach out to us. No job description is perfect – we may find an even more suitable opportunity that is a better fit for you.

How this job compares

Set against the 2,189 open Scientist jobs on Olive Jobs, counted November 2, 2026.

Pay
  • This postingNot listed
  • Massachusetts median$110–156K/yr143 salary ranges
  • US median$31–38/hr95 hourly ranges
Openings
Olive Jobs lists 200 open Scientist jobs in Massachusetts and 2,189 across the US. Under 1% of them nationwide are listed as remote or flexible.
Hiring the most in Massachusetts
Experience
This posting asks for at least 5 years of experience; Scientist postings that state a minimum ask for 3 years at the median (1,619 postings).
Education
1,160 of the 2,189 open Scientist jobs (53%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 2, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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