Data Scientist, Unlearn.AI
$145-180k
2+ days a week in office
Generative machine learning methods for medicine
Job no longer available
Generative machine learning methods for medicine
21-100 employees
Job no longer available
$145-180k
2+ days a week in office
21-100 employees
Company mission
To advance artificial intelligence to eliminate trial and error in medicine.
Role
Who you are
- The ideal candidate has a strong understanding of the challenges of working with clinical data and has proven experience in both data science and software engineering
- Track record of using data science to solve challenging problems
- 2+ years in a related role
- Fluency in Python and essential data science libraries (numpy, pandas, etc.) Demonstrated experience in collaborative software development
- Experience or interest in solving data science problems for healthcare
- Experience or interest in working with multidisciplinary teams that include scientists, engineers, and statisticians. B.S. (advanced preferred) or related degree in a quantitative discipline
- Able to come into either our San Francisco or Boston office at least two days a week
What the job involves
- Data Scientists working on our Data Tools teams at Unlearn are responsible for building world-class internal data products that enable fundamental advancements in machine learning and Unlearn’s solutions for driving clinical trial timelines towards zero
- Data Scientists work in multi-disciplinary teams and build high-quality software that consolidates clinical data from a variety of different sources into a cohesive machine learning-ready dataset. These teams work across disease areas, constantly learning and growing their capability to deliver innovative solutions around clinical data
- Build powerful software tools to transform clinical data, observational study, and electronic health data into tidy datasets that empower machine learning
- Analyzing clinical datasets and understanding outcome measures, biomarkers, and other data measured in clinical trials
- Collaborating with a team of multi-disciplinary scientists and engineers to build high-quality data products that leverage well-organized data, domain knowledge, and insightful data analysis and documentation
Our take
Clinical trials supporting the development of new drugs typically drag out for a number of years. With the root of this problem being the lack of qualified participants, especially when drugs reach critical phase 3 studies, which often require hundreds or thousands of participants to test the investigational drug.
Machine learning generative AI startup, Unlearn.AI, is looking to tackle this challenge and transform the way clinical trials are performed. The company specializes in clinical trial optimization through its proprietary technology, called the "Digital Twin", which creates a virtual replica of a patient population in order to simulate the effects of different treatments. Through this approach, researchers are able to run clinical trials with smaller sample sizes, reducing the time and costs associated with traditional clinical trials.
Since its inception in 2017, Unlearn.AI has worked with a number of pharmaceutical companies as well as academic institutions in order to improve clinical trial designs and accelerate drug development efforts. With a bright future on the horizon for the AI startup, Unlearn.AI has the potential to revolutionize healthcare, diagnostics, and treatment.
Steph
Company Specialist at Welcome to the Jungle
Insights
28% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Feb 2024
$50m
SERIES C
Mar 2023
$15m
LATE VC
Total funding: $130.7m
Company benefits
- 100% employer-covered medical, dental, and vision insurance for you and your family
- Company-paid life insurance, AD&D insurance, short-term/long-term disability insurance
- 401k plan with generous matching
- Paid parental leave
- Professional development budget to attend conferences, workshops, classes, and more
Company HQ
Yerba Buena, San Francisco, CA
Leadership
Charles Fisher
(CEO)Graduated from Harvard University with a Ph.D. in Biophysics. Previously worked as a Machine Learning Engineer at Leap Motion, as well as a Principal Scientist at Pfizer.
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