There are 22M+ Americans who suffer from treatment-resistant mental health conditions, meaning they’ve failed two or more conventional treatments. Our mission is to further innovative mental health treatments (ranging from FDA-approved psychedelic medicines to neuromodulation to digital therapeutics to novel molecular approaches) for those patients who are suffering the most. We do this by empowering providers, improving patient care, and accelerating research. Our electronic medical records software is used by mental health doctors and their patients across the US. We analyze the data to help the doctors deliver better care and also offer insights to help research and development of new treatments that actually work.
Backed by top-tier investors (e.g. General Catalyst, Future Ventures, Tiger Global, Y Combinator, Jerry Yang, Joshua Kushner, etc.), Osmind’s team consists of mission-driven experts from across tech and healthcare. We’re a tight-knit group of intellectually rigorous, highly collaborative, deeply caring, and fun team members. We’ve been featured in publications such as Forbes and Crunchbase News.
We are a Series A funded Public Benefit Corporation (PBC) building something that actually moves the needle on the global mental health crisis. (See here for an article our cofounder Jimmy wrote about PBC’s.) We are searching for a Data Scientist who will use multimodal data from electronic health records, patient-reported outcomes, and other clinical and digital data sources to generate cutting-edge, personalized insights for psychiatric providers and researchers.Let’s transform mental healthcare, together.
What you’ll do
- Be a data leader in the burgeoning field of precision psychiatry and “big data psychiatry” — lead the development of novel algorithms to usher in a new era of mental health. You will play a major role in creating tools that finally help psychiatrists treat patients in a personalized manner, provide objective measurements of mental health, and help researchers develop new treatments.
- Be a hands-on individual contributor on the Data Science team with a solid grasp of relevant technical approaches. Work on projects leveraging real-world healthcare data: perform feasibility analyses, develop algorithms, and create and maintain dashboards for reporting life sciences project operations metrics. Support research projects with activities including data cleaning, modeling, and visualization.
- Work with COO, VP Life Sciences, VP Medical Affairs, Medical Director, data engineers, quantitative scientists, and clinical researchers to ask and answer important scientific and clinical questions with true patient impact. Interface with these internal stakeholders as well as directly with external life sciences partners to understand data needs and define research approaches for their pressing research questions.
A successful first year may include
- Curating customized datasets and performing analytics focused on answering specific research questions posed by academic research collaborators, therapeutics companies, or internal scientists – for example, whether certain concomitant medications decrease the antidepressant efficacy of ketamine infusion therapy, or whether changes in energy and activity precede changes in mood after treatment with rapid-acting antidepressants, or whether certain changes can predict adverse events such as a suicide attempt, or other high-impact research questions.
- Creating high-quality clinical research variables from structured and unstructured electronic health records, outcomes data, digital data, etc., using machine learning methodologies with statistical rigor.
- Building models for ML-extracted variables (such as diagnoses, comorbidities, adverse events, medications, hospitalizations, treatment data).
- Degree in a quantitative discipline with 3+ years of meaningful hands-on experience with analytical methodologies and messy data (e.g. electronic health records, clinical outcomes data, medical claims data, etc). In other words, you’re very well versed in descriptive statistics.
- Experience conducting statistical inference (ie: hypothesis testing, inferring population attributes from samples, appreciating the p-value and its limitations, etc.)
- A track record of designing and engineering complex features (ie: imputing activity levels from location readings, imputing sleep duration from a variety of variables, etc.)
- Experience building categorical and continuous predictive models (ie: classifiers, regressors, etc.)
- Strong familiarity with health data analytics tools, such as SQL, R, Python (Pyspark and Tableau a plus)
- Willingness to work out of our office in San Francisco 2-3 days per week (public health situation permitting)
- Interest in revolutionizing mental health care and neuropsychiatry
- Advanced (e.g. PhD, MS) degree in a quantitative field
- Health tech startup experience, demonstrating that you can thrive in our fast-paced startup environment
- Hands-on experience working on healthcare data or RWE including familiarity with healthcare data standards and terminologies (e.g. ICD-10, SNOMED CT, LOINC, RxNorm, etc.)
- Prior relevant experience working with clinical data in some capacity; familiarity with clinical data such as labs, vitals, chart notes, medications, etc.
- Experience working with HIPAA
- Familiarity with the pharmaceutical industry’s strategy and business processes, including clinical trials, new drug introduction, and clinical operations
- Competitive salary and equity package.
- 100% employer contribution to healthcare insurance (medical, dental, vision) and 50% contribution for dependents
- 401K matching
- Unlimited PTO
- Flexible working hours to match your style. Hybrid working style with a mix of work-from-home and in-office. In-office in San Francisco (Potrero Hill) 2-3 days a week
- In-office perks: food and lunch, snacks and drinks, happy hours, etc.
- Contribute to one of the most innovative areas of medicine: frontier neuropsychiatry.
- Be part of an all-star team that is intellectually rigorous, highly collaborative, deeply caring, and likes to have fun.
- Tremendous growth opportunity and autonomy given we’re a high-growth startup.