Sr. Director, Data Science Patient Safety

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

As the Senior Director of Data Science, Patient Safety you will lead our Patient Safety and Pharmacy Operations Analytics team. You will engage with key leaders across the enterprise to define strategic roadmap for the use data science to improve clinical outcomes. You will lead design and development and deployment of analytics solutions and measure their impact of health outcomes of CVS patients and customers. You will manage multiple high-profile work streams with urgency, be accountable for delivering quality results, and be able to present these results to senior leadership within the company.

Your core responsibilities will include:

• Lead initiatives to improve pharmacy operations, reduce prescription errors and improve patient outcomes across CVS Retail, Specialty Mail, Caremark and other businesses.
• Oversee the development of analytics solutions that deploy advanced machine learning and artificial intelligence methods for a wide range of patient safety and clinical topics in Retail, such as:
  • Prescription Verification: build machine learning models that can validate the correctness of a script in real-time by leveraging prescription attributes, patient profiles, diagnosis codes, and other pharmacy information.
  • Clinical Decision Support Engine: develop machine learning models to prioritize clinical alerts shown to pharmacists in real-time, based on clinical/operational relevance and impact, in order to prioritize high-value alerts and suppress low-value prompts. Overall goal will be to drive up the signal-to-noise ratio and reduce Pharmacy Teams’ “alert fatigue.”
  • Prescription Fraud Detection: develop unsupervised and semi-supervised models that can autonomously monitor prescription patterns in order to flag potentially fraudulent behavior to Pharmacy teams.
• Lead Pharmacy Operations and Patient Safety Analytics team including laying out strategic vision for the team, recruiting, mentoring and developing people, building capabilities in data assets, operational processes and technology, deepening team expertise in AI and ML
• Use clinical expertise and technology depth to engage with key leaders across the enterprise to identify new applications of artificial intelligence in patient safety topics
• Recruit, develop and mentor data scientists, contribute to their learning and training agenda, knowledge sharing, and provide input on technology stack

Required Qualifications

• Strong leadership skills, strategic mindset and experience leading highly technical teams focused on deploying AI-based solutions in healthcare
• 5-10 years of experience leading development of advanced machine learning solutions in a healthcare setting.
• Deep and broad data science expertise including with supervised, unsupervised and reinforcement learning approaches, natural language processing, modern deep neural network architecture and implementation.
• 5-10 years experience in health policy, epidemiology, medical research or related area including applications of quantitative methods to improve clinical outcomes
• Practical experience with modern data and computing infrastructure including deploying machine learning models in production environment
• Ability to communicate effectively in a clear, logical, and consistent manner with all audiences, with varying levels of technical background.
• Proven ability to establish and maintain collaborative relationships with non-analytic business partners, including executive leadership. Ability to elicit business needs and formulate, propose and refine analytic solutions, in order to meet the business needs and to drive efficiency, effective improvements, and business value.
• Excellent project management skills with ability to lead and engage in multiple projects and initiatives and appropriately, prioritize her/his own time as well as that of the direct reports, and adjust priorities as needed to meet deadlines.
• Expert level programming skills in Python, R, TensorFlow, or other data science environment; robust data management and reporting skills, understanding of deploying machine learning models in real time production environments including cloud (Azure, AWS), Spark-based systems, etc.
• Highest level of attention to detail when working within legal and compliance regulations, primarily around HIPAA, patient safety work product, and attorney/client privilege while working with sensitive, confidential, and protected data.

Preferred Qualifications

• MD or equivalent health research experience is a strong plus.
• Education
• Ph.D. in Computer Science, Mathematics, Engineering or related field is required.