Position Overview:We are seeking a talented Data Scientist to join our team of researchers. The ideal candidate will have a strong foundation in machine learning and statistics with an interest in causal inference. A couple of recent preprints we've released to get a sense of the challenges:
- Robust CATE Estimation Using Novel Ensemble Methods. (https://arxiv.org/abs/2407.03690)
Key Responsibilities:Technical Development:
- Implement and optimize ML algorithms, with a focus on causal ML applications in clinical trials
- Collaborate with senior data scientists to develop and improve our analytical platforms
- Work alongside clinical and biological experts to translate complex problems into technical solutions
Research & Analysis:
- Conduct rigorous statistical analyses of both randomized and observational data
- Develop and validate methods for responder identification and treatment effect estimation
- Document and present methodologies and results for internal and external stakeholders
Collaboration:
- Work cross-functionally with engineering and product teams
- Contribute to technical discussions and peer code reviews
- Support the preparation of technical documentation and research papers
Qualifications:Education:
- Master's in Computer Science, Statistics, Data Science, Engineering or a related field
- Ph.D. is an advantage but not required
Experience:
- 3+ years of experience in data science or machine learning roles
- Experience with ML in a practical research or industry setting
- Background in statistical modeling and analysis
Skills:
- Strong programming skills in Python (R in addition - an advantage)
- Proficiency in statistical analysis and machine learning
- Experience with data visualization and communication of technical concepts
- Strong analytical and problem-solving skills
Preferred:
- Familiarity with causal inference concepts
- Experience in healthcare or biotech industry
- Experience with large-scale data processing
What We Offer:- Join us on a mission to bring more effective drugs to more patients.
- The opportunity to work with an amazing team passionate about making a real-world impact.
- Extremely hard and diverse problem setting, in which the team is pushing the envelope.
- A collaborative and dynamic startup environment.
- Professional growth and development opportunities.
