• Responsible for leading and executes end‑to‑end data management activities • Ensure high‑quality, complete, and accurate information across diverse and complex projects • Maintain continuous quality improvement of data management-related processes • Keep abreast of changes in internal and external requirements • Develop and maintain processes for data management • Assist in development of data management-related processes • Proactively drives quality deliverables • Collaborate with internal and external stakeholders to ensure all data is complete, timely, and accurate • Work with cross-functional stakeholders to understand implications of updates • Lead discussions with healthcare organizations to educate on Pfizer requirements

• Utilize data analytics tools to support the design and implementation of claim fraud detection and prevention initiatives. • Compiles, cleans, organizes and analyzes complex data to understand fraud results. • Develop and maintain comprehensive data models to identify fraud patterns and trends. • Pilot technical solutions to enhance both operational and data analysis capabilities for fraud detection and prevention. • Collaborate with internal partners such as IT, Legal, Compliance, and Claims to ensure alignment and effective fraud mitigation solutions. • Design and operate reports to measure the effectiveness and loss cost containment of fraud mitigation tools, processes, and initiatives. • Build automated self-service reports to track referrals, assignments, performance metrics, and outcomes of claim fraud. • Develop a consistent communication strategy to keep all stakeholders informed and engaged. • Develop and maintain strong relationships with key departments to foster a culture of transparency and trust. • Ensure timely and effective communication with all relevant parties during fraud investigations.

• Responsible for designing evaluation frameworks, testing methodologies, and telemetry analysis for agentic systems, with working knowledge of LangChain and LangGraph to support and enhance engineering efforts. • Build, validate, and optimize data models focused on generative AI and large language models. • Create and refine methods to measure AI model and agent performance, quality, and impact. • Collaborate with product and engineering teams to inform and support integration of AI solutions (e.g., Gemini, OpenAI, Azure AI). • Stay current on advances in data science, machine learning, and generative AI. • Mentor junior data scientists and engineers. • Communicate clearly with stakeholders, presenting insights and recommendations. • Apply statistical, econometric, and machine learning methods to generate actionable insights and support decision-making. • Identify, integrate, and leverage key data sources to enhance analytics. • Develop scalable data structures and analytic products. • Lead end-to-end analytics and modeling projects, including data gathering, feature engineering, model development, evaluation, and monitoring. • Provide insights to encourage data-driven decision-making throughout the organization. • Mentor teams on data science best practices and contribute thought leadership through blogs or articles. • Develop and deliver training on analytics tools and data science techniques (e.g., Alteryx, Tableau).

Join the transformative team at City of Hope, where we're changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. City of Hope’s growing national system includes its Los Angeles campus, a network of clinical care locations across Southern California, a new cancer center in Orange County, California, and treatment facilities in Atlanta, Chicago and Phoenix. Our dedicated and compassionate employees are driven by a common mission: To deliver the cures of tomorrow to the people who need them today. ** This is a Fully Remote Opportunity within the United States** The Data Scientist in this role will query and analyze large complex datasets to discover insights to apply to an evolving cancer care delivery environment. The Data Scientist will use data mining, statistics and machine learning to understand relationships and patterns in data, build predictive models and propose actionable solutions. As a successful candidate, you will: - Collaborate with administrative leaders, clinicians and IT specialists - Query large datasets from multiple systems - Build machine learning models - Design and implementation of pilots for validation and optimization of models in real time - Produce technical documentation, visualizations and presentations - Project management for complex tasks - Completes own work independently - Performs other related duties as assigned or requested. Your qualifications should include: - Master’s degree with 0+ years of experience; or Bachelor’s degree with 3+ years of experience Preferred: - Familiarity with a health care environment and EHR data - Familiarity with time series, deep learning, and Natural Language Processing (NLP) - Proficient designing, training, testing, deploying, and monitoring machine learning models to solve a wide array of problems - Familiarity with cloud services like Microsoft Azure and version control systems (Git) - Experience with Generative AI and Large Language Models (LLMs), RAG, fine-tuning, embeddings, prompt engineering, and agentic workflows - Awareness of the most recent trends and developments in the Data Science / Machine Learning fields - Experience with Snowflake a plus - Proficient developing machine learning models for classification, regression and clustering - Experience with relational databases and SQL queries. - Proficient in Python and its machine learning libraries like pandas, scikit-learn, PyTorch, LangChain, etc - Familiar embedding LLMs into workflows with packages like LangChain and LangGraph - Advanced knowledge of probability, statistics, and scientific computing - Ability to work independently and use creative approaches to problem- solving Capable of turning questions into testable hypotheses, extracting data from complex databases, creating and evaluating statistical models Experience in data visualization and ability to communicate results to a non-technical audience Experience in completing end-to-end projects with minimal to no supervision Experience in being a part of big projects with many internal and external teams involved Experience managing collaborative data science projects City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location. City of Hope is an equal opportunity employer. To learn more about our Comprehensive Benefits, please CLICK HERE.