Description

Job Details 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. The Lead Data Science and Machine Learning (ML) directs and executes Ontada's technology roadmaps in ML and Natural Language Processing (NLP) Data Platform roadmap through close collaboration with Ontada commercial, chart abstraction and engineering teams. He/she follows the agile development methodology to rapidly iterate prototypes and scales them to platform re-usable capabilities in order to accelerate data product and insight delivery to health care and life science customers, while maintaining sustainable growth. Thought leadership in ML/NLP and excellent communication skills with the ability to resolve competing priorities are required for this position. Key Responsibilities: Data Science and ML Leadership: Develop a comprehensive strategy of Data Science taking into account Ontada's overall vision, the evolving health IT and data ecosystem, and productive application in AI Develop state-of-the-art NLP or AI pipeline to meet Ontada business mission timelines Present and communicate the ML/NLP strategy and project to all stakeholders in Ontada and McKesson leaderships, as well as customers and prospects Direct full life cycle ML/NLP solutions, from planning, designing, technical implementation, troubleshooting, deployment, validation, and maintenance Be accountable to the data science backlog and constantly evolve it based on the latest changes in the business Manage conflicting priorities across different stakeholders Perform code reviews to guarantee high quality products Oversee technology implementation to automate data processes and inferences Direct annotation workflow and abstractor training process development Orchestrate across a multi-disciplinary team to create a unified strategy that drives business value Develop trust partnership with stakeholders through transparency and incremental delivery of value Manage third-party vendors Evaluate innovative technologies and tools prior to wider business adoption Typical Minimum Requirements: 10+ years of experience in advanced analytics, machine learning, and natural language processing Critical Skills: Experience in mining Claims and EHR (Electronic Health Records) data, preferably oncology related data Experience managing full lifecycle, from research to production, of machine learning data products Experience in Optical Character Recognition (OCR) and NLP for unstructured data analysis Knowledge in Large Langue Model (LLM) and Retrieval Augmented Generation (RAG) Knowledge of data curation and analysis packages (e.g., NumPy, Keras, PyTorch, Pandas, scikit-learn) Knowledge of NLP libraries, ontology-based and deep learning-based libraries, (i.e., Huggingface, SpaCy, NLTK, cTAKES, MetaMap, or John Snow Labs) Experience with modern cloud technologies in AWS and Azure Experience with ML workflow orchestration tools (e.g., Airflow, MLflow) Experience with Github, JIRA and Confluence Solves problems in unique ways by drawing from background and experience working in an array of contexts Experience in working in root cause identification and analysis Experience with healthcare data, real-world data, or clinical data Experience in team culture building with growth mindset Additional Skills: Excellent written and verbal communication skills Experience working in the life sciences or the bio/chemical research field Experience in oncology data and clinical workflow Demonstrated entrepreneurial mindset and self-direction, ability to mentor others and willingness to learn new techniques Willingness to jump into projects and complex environments to make sense of ambiguous details in multiple domains Education: MS or PhD in data science or related field

Role and Responsibilities

• Key Responsibilities: Data Science and ML Leadership: Develop a comprehensive strategy of Data Science taking into account Ontada's overall vision, the evolving health IT and data ecosystem, and productive application in AI Develop state-of-the-art NLP or AI pipeline to meet Ontada business mission timelines Present and communicate the ML/NLP strategy and project to all stakeholders in Ontada and McKesson leaderships, as well as customers and prospects Direct full life cycle ML/NLP solutions, from planning, designing, technical implementation, troubleshooting, deployment, validation, and maintenance Be accountable to the data science backlog and constantly evolve it based on the latest changes in the business Manage conflicting priorities across different stakeholders Perform code reviews to guarantee high quality products Oversee technology implementation to automate data processes and inferences Direct annotation workflow and abstractor training process development Orchestrate across a multi-disciplinary team to create a unified strategy that drives business value Develop trust partnership with stakeholders through transparency and incremental delivery of value Manage third-party vendors Evaluate innovative technologies and tools prior to wider business adoption