Senior Director, Customer Data Analytics & Data Science - Healthcare Analytics Solutions

Overview

Healthcare Analytics Solutions (HAS) is an innovative team within Quest Diagnostics that leverages Quest data to develop products and services to solve the challenges and improve outcomes in healthcare across many different markets (Pharma, Clinical Trials, Health Plans/Payers, Hospitals/Health Systems, and Public Health agencies).

 

The Senior Director, Customer Data Analytics and Data Science is a strategic leadership role responsible for driving the development and delivery of data and analytics solutions to customers. The Senior Director will lead a team of data engineers, data analytics professionals, and data scientists to prepare and deliver data products, impactful analytical insights, predictive models, and visualizations to customers. In addition, the role will collaborate across the organization including product management, data engineering, sales, and development to ensure analytics solutions align with the broader product roadmaps and meet customer expectations.

Responsibilities

• Provide leadership and management, and direction to a team of data scientists, data analysts, and dashboard developers
• Manage and optimize the creation and delivery of data licensing, data related analytics, and dashboard products.
• Build, mentor, and lead a high-performing team of analysts, data scientists, and dashboard developers fostering innovation, collaboration, and career growth.
• Champion best practices in data governance, security, and regulatory compliance, and ensure responsible use of data internally and with customers.
• Partner with the HAS leadership team, including business leaders, other solution development leaders, and the advanced analytics team to drive innovation and growth in support of the HAS business strategy.
• Establish consistent, repeatable processes to support product and revenue growth and promote alignment with industry standards.
• Coordinate and collaborate with the Quest Technology Organization including the analytics and architecture teams, as well as analytics professionals throughout the organization to improve the enterprise data science development environment and suite of tools.
• Collaborate across HAS and QT to develop and promote best practices for data management and ETL.
• Test and ensure HAS solutions yield high-quality, high-confidence results in accordance with Quest’s quality standards and expectations of excellence in delivery of client services and solutions.
• Clearly document and communicate objectives, requirements, and designs at these different levels of abstraction to both technical and non-technical audiences.
• Create and manage operating costs, capital, schedule, and human resources costs of proposed solutions. Compare, contrast, and prioritize alternative approaches while assessing risk both quantitatively and qualitatively.
• Support a culture of continuous improvement with a will to win.

Qualifications

• Advanced degree in engineering, science, mathematics, or other field related to data science and advanced analytics.
• A minimum of 12 years of relevant experience in big data, analytics, machine learning, and predictive modeling preferred.
• A minimum of 5 years of experience in data preparation, management, and delivery.
• Demonstrated experience creating and managing workflow and delivery processes.
• A minimum of 5 years of experience managing remote teams with demonstrated leadership skills, project management skills, strong written and verbal skills, and organizational skills. Proven ability to work in a highly matrixed organization.
• Expert knowledge and experience developing analytics solutions in a cloud environment using modern data science tools, programming languages, and libraries (Cloud certification preferred).
• Knowledge of SAS (SAS Studio, SAS Enterprise Guide, SAS Enterprise Miner, Viya).
• Expert knowledge of the latest machine learning and data visualization tools and methods as applied in business contexts.
• Experience with the Machine Learning Life Cycle with experience leading advanced analytics and machine learning projects from problem formulation, to research and exploration, through development and successful deployment.
• Successful application of advanced quantitative analyses and statistical modeling that positively impact business performance.
• Experience and expertise with probability and statistics, inclusive of machine learning, experimental design, and optimization.
• Experience in scripting languages and rapid prototyping skills; including but not limited to SQL, Python, Perl, Java, VB.
• Skill in statistical and modeling packages such as SAS, Statistica, Matlab, R, visualization and other advanced analysis tools.
• Ability to effectively summarize results from an