Two Sigma Ventures

The Opportunity

The heart of insitro’s strategy is the combination of novel, cutting edge methods in machine learning, human biology at scale and molecular discovery that address key bottlenecks in the drug development pipeline. We are searching for an outstanding physician scientist with expertise in the utilization of human imaging, soluble biomarker, germline and somatic genetic data sets to help guide our oncology drug discovery strategy. In this role you will be responsible for aligning and advancing our internal and partnered programs with a relentless focus on unequivocally improved patient clinical outcomes. You will work with cross-functional teams and serve as a bridge between ML enabled laboratory models, internal and collaborative drug discovery teams, and human data at scale to inform our oncology drug discovery and development strategy. You will inform the strategy for using clinical data at scale combined with advanced ML to inform our understanding of disease progression, treatment resistance, and for identifying clinically relevant patient subpopulations. You will be an integral part of the rapidly expanding Oncology Therapeutic Area and work closely with the executive team to develop an advanced machine learning-enabled drug discovery strategy.

Your primary duties will be to:

• Play a key strategic role in integration of the patient perspective to inform disease modeling and drug discovery efforts, including understanding the standard of care, areas of unmet need, and identifying viable target-patient profiles.
• Partner with colleagues in data science & machine learning (DSML) and in corporate development to identify critical data assets and/or commission the generation of data for discovery efforts in oncology.
• Collaborate closely with data science & machine learning (DSML) colleagues to define machine learning (ML) models for clinical data to inform our understanding of patient trajectory and patient subpopulations and to identify novel endpoints for clinical trials.
• Assist drug discovery teams to prepare IND-enabling data packages in alignment with clinical development objectives.
• Longer-term, partner with market planning and commercial development colleagues on market research and target-patient profiles for new programs.
• Contribute as a clinical area expert dedicated to translational approaches and early clinical development.
• Participate in efforts to model and design ML-enabled clinical trials for internal and/or partnered programs.
• Participate in strategic overview of presentations, publications, and internal/ external communications along with accountable project and program leadership.

You will be joining as the founding team of a biotech startup that has long-term stability due to significant funding, but yet is very much in formation. A lot can change in this early and exciting phase, providing many opportunities for significant impact. You will work closely with a very versatile team, learn a broad range of skills, and help shape insitro’s culture, strategic direction, and outcomes. Join us, and help make a difference to patients!

About You

• MD or MD/PhD in a technical field (oncology, immuno-oncology, cell & molecular biology, etc.) or equivalent, with 8+ years of postdoctoral experience.
• Experience working with cancer patients, patient data, patient trajectories/disease progression and clinical trial design.
• Experience with biomarker data sets such as; clinical imaging, proteomics, metabolomics, and transcriptomics.
• Familiarity with pioneering oncology translational models (patient-derived organoids, patient derived xenografts, primary metastatic etc)
• Experience working as part of a high-performance team, including goal setting and contributing to a culture of effective, high-quality methods development and reducing those methods to a practical implementation.
• Excellent teamwork, communication, time management and organization skills
• Strong verbal and written communication skills across all levels both within an organization and with external partners.