McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. Job Description Join the growing Ontada team, backed by a Fortune 8 company, and help transform oncology care. Ontada develops technologies that support oncology providers in delivering evidence‑based, personalized care and provides insights that help biopharma accelerate drug development, optimize clinical trials, support treatment decisions, and guide commercial strategies. We are seeking a self‑motivated, collaborative, and detail‑oriented Data Scientist to support our Data Science & Analytics team in delivering high‑quality data and insights to Life Sciences customers. Position Summary Ontada leverages deep expertise in data science, analytics, and real‑world clinical data to deliver clinical data products and insights across the drug development and commercialization lifecycle. Our work helps Life Science partners understand markets, demonstrate value, inform decisions, and evaluate real‑world treatment effectiveness. The Data Scientist will work with complex business questions using our in‑house EMR/EHR data. Responsibilities include data preparation, analysis, quality assurance, and maintaining analytical tools and pipelines. This role involves acquiring and validating raw data, performing analyses, contributing to tooling improvements, and producing both mock‑up and production‑ready deliverables. Success requires strong analytical skills, experience with longitudinal patient‑level data, and excellent communication abilities. Key Responsibilities - Apply analytical rigor to longitudinal patient‑level data, synthesizing business rules, methods, and client objectives with limited oversight. - Create clear, compelling materials that communicate insights from clinical data and present findings to both technical and business audiences. - Build reproducible analytical workflows and advanced algorithms in Databricks (PySpark and SQL) to prepare and analyze large‑scale healthcare datasets (EHR, medical/pharmacy claims, RWD). - Ensure accuracy and customer readiness by delivering high‑quality datasets and reports that meet exact specifications and highlight meaningful insights. - Contribute to quality and consistency through self‑review and peer review of methodologies, code, and deliverables. - Manage multiple projects in a fast‑paced environment while maintaining strong analytical and documentation standards. - Develop data visualizations and dashboards to communicate trends and enable data‑driven decision‑making for clients. Minimum Requirements - Bachelor’s / Master’s degree, with a focus in Data and Analytics, Information Sciences, Healthcare, Statistics, Computer Science or related fields strongly preferred - 3+ years of experience of relevant experience - Able to work Central Time Zone hours Critical Skills Communication & Stakeholder Engagement: Strong interpersonal, written, and verbal communication skills with experience collaborating across cross‑functional teams and presenting insights to diverse audiences. Able to clearly explain complex data issues. Experience gathering and documenting requirements is a plus. Healthcare Analytics Expertise (3+ years): Hands‑on experience analyzing large real‑world healthcare datasets (EHR/EMR, medical and pharmacy claims, labs, etc.) and translating complex findings into clear, actionable insights. Solid understanding of treatment pathways, patient journeys, and real‑world evidence (RWE) analysis. Advanced Programming: At least 2 years of practical experience with Python, PySpark, and SQL in Databricks or similar cloud analytics platforms to build and deploy repeatable, production‑ready data pipelines. SAS experience is a plus. Data Preparation & Quality Management: Skilled in data wrangling, cleansing, transformation, and preparation for final data lock, ensuring accuracy, reproducibility, and adherence to quality standards. Strong grasp of real‑world data nuances and limitations. Independent & Proactive Work Style: Self‑starter who delivers high‑quality work with minimal supervision in a fast‑paced environment. Collaboration & Team Effectiveness: Able to work independently and collaboratively while contributing positively to team goals. Curiosity & Problem Solving: Demonstrates intellectual curiosity and creativity in solving ambiguous analytical challenges. Precision & Attention to Detail: Strong commitment to analytical accuracy, documentation, and reproducibility. Continuous Learning: Motivated to stay current with emerging analytical methods, tools, and industry trends. Core Productivity Tools: Proficient in Microsoft Word, Excel, and PowerPoint for documentation and presentations. Additional Preferred Skills - Experience in healthcare or life sciences consulting or analytics roles within biopharma. - Oncology experience. - Experience within EMR, CRO, or transaction‑processing environments. Work Authorization Requirement At this time, we can only consider applicants who are legally authorized to work in the United States and who do not require current or future sponsorship for employment visas. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $109,900 - $183,100 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: careers.mckesson.com. McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process. If you require accommodation please contact us by sending an email to Disability_Accommodation@McKesson.com. Join us at McKesson!

• Responsible for designing, developing, and deploying intelligent agents using LangChain and LangGraph frameworks to optimize conversational AI workflows. • Build, deploy, and optimize data models focused on generative AI and large language models. • Create and refine methods to measure AI model performance and impact. • Collaborate with product and engineering teams to integrate 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 projects including data gathering, feature creation, modeling, deployment, 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). • Explore and apply new data science tools and methodologies to maintain innovation.

• Responsible for designing, developing, and deploying intelligent agents using LangChain and LangGraph frameworks to optimize conversational AI workflows. • Build, deploy, and optimize data models focused on generative AI and large language models. • Create and refine methods to measure AI model performance and impact. • Collaborate with product and engineering teams to integrate AI solutions (e.g., Gemini, OpenAI, Azure AI). • Stay current on advances in data science, machine learning, and generative AI. • 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 projects including data gathering, feature creation, modeling, deployment, 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). • Explore and apply new data science tools and methodologies to maintain innovation.

Role Description This role offers a high-impact opportunity to advance AI- and ML-driven solutions within a performance management platform. You will leverage large-scale HR, engagement, and behavioral datasets to design, train, and deploy machine learning models that provide actionable insights for managers and HR leaders. Collaborating closely with software and data engineering teams, you will build scalable pipelines, engineer features, and develop context layers that power intelligent AI agents. Your work will directly influence the platform’s capabilities, accelerating employee engagement, performance, and retention. This role requires a blend of advanced statistical analysis, applied machine learning, and operational execution within a fast-paced, high-accountability environment. You will be a key contributor to AI initiatives that elevate the product’s intelligence and business impact, while mentoring teams and promoting best practices in data science and MLOps. - Conduct exploratory data analysis and statistical modeling on large structured and unstructured datasets to uncover insights that inform AI models and product decisions. - Design and implement machine learning models, including supervised, unsupervised, and representation-learning approaches, to enhance platform capabilities. - Engineer features and build knowledge representations to enrich AI agents and support intelligent workflows. - Develop high-quality training datasets, including annotations, evaluation frameworks, and benchmarks for model development and validation. - Collaborate with engineering teams to operationalize models, ensuring scalability, reliability, and integration with product architecture. - Continuously evaluate model performance, iterate on features and pipelines, and adjust strategies based on business needs and experimental outcomes. - Work cross-functionally with product, design, and engineering teams to translate business problems into data science solutions and actionable insights. Qualifications - BS or higher in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field, or equivalent practical experience. - 7+ years of experience in data science, applied machine learning, or statistical modeling in production environments. - Strong statistical foundation and expertise in analyzing complex datasets to extract meaningful patterns and actionable insights. - Hands-on experience developing, evaluating, and deploying ML models with measurable business impact; familiarity with LLMs and embeddings is a plus. - Proficiency in Python and SQL, with experience building data pipelines, training models, and performing large-scale data analysis. - Experience with modern data platforms, data warehouses, and distributed processing systems. - Familiarity with MLOps practices, including model training, versioning, deployment, and lifecycle management. - Strong collaboration and communication skills to explain complex technical concepts to non-technical stakeholders. Requirements - Competitive annual base salary: $132,500 - $170,500. - Participation in annual discretionary company bonus program and equity awards. - Medical, dental, and vision insurance with company cost subsidies. - Short-term, long-term disability, and life insurance coverage. - Flexible Time Off program, generous parental leave, military leave, and paid company holidays. - Sabbatical program and professional development support. - 401(k) plan with 4% employer match after 6 months. - Remote work flexibility and collaboration with industry-leading experts in AI, HR technology, and data science. - Supportive programs for mental health, wellness, and inclusive benefits for employees and their families.