Senior Manager, Data Scientist

Summit Therapeutics Inc. is a biopharmaceutical oncology company with a mission focused on improving quality of life, increasing potential duration of life, and resolving serious unmet medical needs. Our core values include integrity, passion for excellence, purposeful urgency, collaboration, and commitment to people. Summit is headquartered in Miami, Florida, with additional offices in California, New Jersey, the UK, and Ireland.

Summit is conducting multiple global Phase 3 clinical studies in oncology, including:

• Non-small Cell Lung Cancer (NSCLC):
  • HARMONi: Evaluates ivonescimab combined with chemotherapy vs. placebo plus chemotherapy in EGFR-mutated, locally advanced or metastatic non-squamous NSCLC (previously treated with a 3rd generation EGFR TKI).
  • HARMONi-3: Evaluates ivonescimab combined with chemotherapy vs. pembrolizumab combined with chemotherapy in first-line metastatic NSCLC.
  • HARMONi-7: Evaluates ivonescimab monotherapy vs. pembrolizumab monotherapy in first-line metastatic NSCLC.
• Colorectal Cancer (CRC):
  • HARMONi-GI3: Evaluates ivonescimab in combination with chemotherapy vs. bevacizumab plus chemotherapy.

Ivonescimab is an investigational therapy not presently approved by any regulatory authority other than China’s National Medical Products Administration (NMPA).

About the role

The Senior Manager, Data Scientist role is part of the Commercial Operations team supporting the U.S. Business Unit—which includes Sales, Marketing, and Market Access. This team enables key business functions and strategic initiatives through data integration, reporting, and advanced analytics. The position provides broad exposure across the U.S. commercial organization by contributing to advanced analytics solutions, with a core focus on executing analytics across diverse data sources and supporting future machine learning initiatives.

Responsibilities

• Design and implement advanced analytical models (e.g., predictive modeling, segmentation, optimization, machine learning) using datasets such as claims, outlet-level sales data, EDI, hub data, real-world data (RWD), specialty pharmacy/distributor data, EMR, and internal commercial datasets.
• Develop and validate algorithms to identify patient journeys, adherence patterns, and treatment pathways.
• Contribute to an evolving data science practice, including problem framing, data exploration and preparation, data integration, machine learning model development, and production.
• Create scoring frameworks (e.g., HCP opportunity models, payer access risk scores, patient conversion likelihood).
• Build statistical and machine learning models for both proof-of-concept and production environments using Python, R, and SQL.
• Partner with stakeholders across U.S. commercial teams to translate business needs into data-driven and machine learning solutions.
• Communicate advantages, limitations, and implications of analytical approaches to non-technical audiences.
• Share technical insights and solutions through design reviews, pair programming, code/model reviews, and team knowledge-sharing sessions.
• Conduct exploratory analysis of new datasets, generate descriptive statistics, identify trends and insights, and propose data engineering opportunities for integration.
• Utilize commercial or open-source analysis platforms daily (e.g., Jupyter Notebook, RStudio, Posit, Microsoft Azure, Neo4j).
• Perform all other duties as assigned.

Requirements

• Experience in biotech, pharmaceuticals, or life sciences required.
• Bachelor’s degree in Data Science, Computer Science, Mathematics, or a related field required; advanced degree preferred.
• Minimum 5+ years of relevant experience with a bachelor’s degree, or 3+ years with a master’s degree, contributing to or executing data science projects.
• Industry experience in customer behavior prediction, customer journey analytics, marketing analytics, or social network analysis is preferred.
• Demonstrated proficiency in Python and/or R.
• Strong SQL skills with hands-on experience working with relational databases; experience with graph databases and Cypher is a plus.
• Familiarity with machine learning and statistical modeling techniques.
• Strong communication and cross-functional collaboration skills.
• Experience developing solutions using text analytics, customer journey analytics, marketing analytics, or recommendation engines.
• Proven ability to explain statistical and machine learning concepts to business stakeholders in clear and meaningful terms.
• Knowledge of statistical and data mining techniques such as hierarchical clustering, network analysis, regression, random forests, text mining, NLP, and data visualization.

Pay

$160,000 - $180,000 USD. Actual compensation packages are based on factors unique to each candidate, including skill set, depth of experience, certifications, and specific work location. The total compensation package may also include bonus, stock, benefits, and/or other applicable variable compensation.