We Come From a Variety Of Backgrounds Ranging From Machine Learning To Marketing—but Regardless Of Where We Come From, Unlearners Share Some Common Traits

• Unlearners are ambitious; we aren’t intimidated by big, challenging goals.
• Unlearners are disciplined experimenters; we break down our big goals into smaller chunks and meet as often as necessary to track our velocity and iterate quickly.
• Unlearners are gritty; we never give up, setbacks just make us try harder.
• Unlearners are receptive to new ideas; in fact, we hate being stuck with the status quo
• Unlearners are storytellers; sharing information with each other and with the world is super important, too important to be boring. And, last but not least,
• Unlearners are team-oriented; we put the mission first, the company second, the team third, and individuals last.

Headquartered in San Francisco, Unlearn was founded in 2017 by a team of world-class machine learning scientists. We have raised venture capital from top tier investors such as Altimeter, Insight Partners, Radical Ventures, 8VC, DCVC, and DCVC Bio, and recently completed our $50 million Series C in January 2024.

If our purpose and culture resonate with you, we invite you to apply. Biostatistician. Biostatisticians lead Unlearn’s work to integrate state-of-the-art ML approaches into the design and analysis of clinical trials. This can be everything from utilizing PROCOVA, a methodology we developed to add power and reduce sample size in phase 2 and 3 trials, to defining and conducting Bayesian or single arm analyses or innovating solutions for custom problems. Biostatisticians at Unlearn work closely with their counterparts at customers as well as broader clinical development teams. We highly value practical experience, the determination and autonomy to own projects end-to-end, and eager collaboration with an excellent and diverse team.

Responsibilities Include

• Define statistical analyses to utilize digital twins to improve the power and lower the sample size requirements of RCTs and to provide a comparator for single arm trials.
• Carry out internal and external case studies to utilize ML-based predictions in clinical trial applications.
• Work with customers in trial planning applications to use digital twins to select and optimize inclusion/exclusion criteria, endpoints, and simulate trial outcomes.
• Author regulatory documents such as SAP and protocol sections or briefing book contributions for clinical trials that use digital twins.
• Present to clients and prospective clients on statistical methodology using digital twins and results of analyses, and represent Unlearn to the broader scientific community.
• Collaborate with internal teams to develop evidence and test methodologies.

Minimum Requirements

• At least 2 years of experience at a pharmaceutical/biotech company or CRO supporting clinical trials.
• MS or PhD in Statistics or Biostatistics.
• Experience writing statistical analysis plans and collaborating with clinical leaders.
• Strong knowledge of SAS and R.
• Experience in clinical trial design and optimization in both placebo controlled and hybrid study designs.

Bonus Points For

• Experience with machine learning applications in clinical research.
• Experience with regulatory interactions.
• Excellent external communication and interpersonal skills.

Benefits & Perks

The following benefits and perks are for full time roles only.

• Generous equity participation
• 100% company-covered medical, dental, & vision insurance plans
• 401k plan with matching
• Flexible PTO plus company holidays
• Annual company-wide break December 24 through January 1
• Commuter benefits
• Paid Parental Leave
• Support for H1B, TN, and E-3 Visa change of employer transfers

Unlearn is an equal opportunity employer.

At Unlearn, we are committed to building a diverse and inclusive workplace, because inclusion and diversity are essential to achieving our mission. If you’re excited about this role, and your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply nevertheless.