Company Overview:

PhaseV (HQ in Boston, R&D in Tel Aviv) is a cutting-edge startup, pushing innovation in the drug development process to bring new treatments to more patients, in a more efficient and precise way. Leveraging the power of advanced causal inference and pushing the boundaries of machine learning, PhaseV detects hidden signals in clinical data and extracts actionable insights for planning the optimal trial. The company's proprietary ML-based platform for adaptive clinical trial design and closed-loop execution enables sponsors to easily and quickly unlock the potential of adaptive clinical trials, reveal the optimal adaptive design to meet their trial objectives and execute more efficient, more precise, and more successful clinical trials. Collaborating with 7 of the top pharmaceutical companies, as well as multiple CROs and biotechs, we are poised to make a significant impact on how drugs are developed and brought to market.

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. This is an integral role on our team with opportunity to interface with our clients directly. Strong communication skills and the ability to navigate ambiguity with a sense of proactiveness is a must. This position offers autonomy and the ability to make an impact on a growing business.

A couple of recent preprints we’ve released to get a sense of the challenges:

• Causal Responder Detection (https://arxiv.org/abs/2406.17571)
• 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, product, and business development teams
• Contribute to technical discussions and peer code reviews