Senior Manager, Data Scientist

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Ivonescimab, known as SMT
112, is a novel, potential first-in-class investigational bispecific antibody combining the effects of immunotherapy via a blockade of PD-1 with the anti-angiogenesis effects associated with blocking VEGF into a single molecule. Ivonescimab displays unique cooperative binding to each of its intended targets with multifold higher affinity when in the presence of both PD-1 and VEGF.

Summit has begun its clinical development of ivonescimab in non-small cell lung cancer (NSCLC), with three active Phase III trials:

• HARMONi is a Phase III clinical trial which intends to evaluate ivonescimab combined with chemotherapy compared to placebo plus chemotherapy in patients with EGFR-mutated, locally advanced or metastatic non-squamous NSCLC who have progressed after treatment with a 3rd generation EGFR TKI (e.g., osimertinib).
• HARMONi-3 is a Phase III clinical trial which is designed to evaluate ivonescimab combined with chemotherapy compared to pembrolizumab combined with chemotherapy in patients with first-line metastatic NSCLC.
• HARMONi-7 is a Phase III clinical trial which is intended to evaluate ivonescimab monotherapy compared to pembrolizumab monotherapy in patients with first-line metastatic NSCLC whose tumors have high PD-L1 expression.

Ivonescimab is an investigational therapy that is not approved by any regulatory authority in Summit’s license territories, including the United States and Europe. Ivonescimab was approved for marketing authorization in China in May 2024. Ivonescimab was granted Fast Track designation by the US Food & Drug Administration (FDA) for the HARMONi clinical trial setting.

The Senior Manager, Data Scientist role is part of the Commercial Operations team supporting the U.S. Business Unit—which includes, but is not limited to, Sales, Marketing, and Market Access. This team enables key business functions and strategic initiatives through data integration, reporting, and advanced analytics.

This position provides a unique opportunity for broad exposure across the U.S. commercial organization by contributing to the development of advanced analytics solutions. A core focus of the role will involve executing analytics on a variety of data sources—including patient claims, EDI shipment data, and unstructured datasets—as well as supporting future machine learning initiatives.

• Design and implement advanced analytical models (e.g., predictive modeling, segmentation, optimization, machine learning) using diverse 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 the 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 one or more commercial or open-source analysis platforms daily (e.g., Jupyter Notebook, RStudio, Posit, Microsoft Azure, Neo4j).
• All other duties as assigned.

• Expe…