Director of Data Science - Machine Learning
May 17
🏡 Remote – Anywhere in California
Description
• Craft a comprehensive Data Science strategy aligned with the organization’s vision, adapting to the evolving health IT and data landscape, and ensuring AI applications align with business goals • Communicate the ML/NLP strategy and projects to key stakeholders including leadership, customers, and prospects • Lead end-to-end ML/NLP solutions, from planning to maintenance, ensuring quality and alignment with business needs • Manage the data science backlog, adjusting priorities based on evolving business needs • Coordinate across stakeholders to manage conflicting priorities • Develop cutting-edge NLP or AI pipelines to support business objectives • Conduct code reviews to ensure product quality • Oversee technology implementation for automating data processes and inference • Lead annotation workflow and abstractor training development • Coordinate a multi-disciplinary team to develop a cohesive strategy that delivers business value • Cultivate trust with stakeholders through transparent, incremental delivery of value • Manage relationships with third-party vendors • Evaluate new technologies and tools for potential adoption • Prioritize value for the team • Continuously assess project and product success to ensure alignment with business objectives • Foster creativity and innovation within the team • Build high-performing teams that deliver data science solutions efficiently • Serve as a visible leader in the data science field, offering mentorship, feedback, and coaching, while promoting community development initiatives
Requirements
• 10+ years of advanced analytics, machine learning, and natural language processing experience • 4+ years of people management experience • Expertise in mining Claims and EHR data, preferably in oncology • Experience managing the full lifecycle of machine learning data products • Proficiency in OCR and NLP for unstructured data analysis • Knowledge of Large Language Models (LLM) and Retrieval Augmented Generation (RAG) • Familiarity with data curation and analysis packages (e.g., NumPy, Keras, PyTorch, Pandas, scikit-learn) • Proficiency in NLP libraries, including Huggingface, SpaCy, NLTK, cTAKES, MetaMap, or John Snow Labs • Experience with AWS and Azure cloud technologies • Familiarity with ML workflow orchestration tools such as Airflow and MLflow • Proficiency with Github, JIRA, and Confluence • Strong problem-solving skills and experience in root cause analysis • Experience with healthcare, real-world, or clinical data • Experience building team culture with a growth mindset
Benefits
• 11 paid holidays • Generous Accrued Time Off increasing with years of service • Generous paid sick time • Annual day of service
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