Senior Director of Data Science 1010 views

The Senior Director of Data Science is responsible for driving data vision, strategy, and execution and ensuring that data science goals and technology investments are aligned with the business’s mission, strategy, and objectives.

Essential Duties And Responsibilities

• Drive data vision, strategy, and execution. Define how the business can create additional value through the development of algorithms and other utilization of its data assets and analytics. Drive alignment and support across the organization through collaboration, communication, and transparency.
• Oversee the data science department, inclusive of data science, algorithm development, data analytics, data engineering and data architecture roles necessary to build the data capabilities to efficiently derive value from data
• Build the business’s data science talent needs through role definition, recruitment, and development of a team of data scientists that will jointly move the business’s agenda forward
• Play a mentorship role to key data science positions, guiding them through the execution of their duties, and encouraging their professional growth
• Work with cross-functional stakeholders to identify and prioritize data science use cases that support the company’s imperatives and objectives and improve customers’ experiences
• Create the process to identify, prioritize, define, and execute data science projects and create transfer mechanisms such as reports, visualizations, requirements, or tools
• Work with product management and engineering stakeholders to define a process around data instrumentation
• Build out a modern data platform that meets the core data provisioning needs of the organization’s data consumers
• Define and support business intelligence and analytics needs
• Create the process and capabilities to feed actionable insights back into departments for continued learning, iteration, and action
• Identify opportunities for data-driven applications that could measurably improve the customer experience and the business’s efficiency through automation and machine learning
• Define the company’s strategy for data distribution
• Free up resources, lower barriers, and increase productivity through process
• Insert data requirements into technology choices and investment decisions
• Participate in defining cross-functional data governance
• Build bridges between business and engineering stakeholders
• Identify and provide tools and training to help others leverage data
• Train and inspire stakeholders to identify opportunities to leverage data science and simulations

Experience Requirements

• 7+ years of work experience in a Data Science domain
• 4+ years of experience in people management and team leadership
• Experience in the digital healthcare industry
• Experience building and leading data science practices and evangelizing/advocating for data science value across the business and to diverse audiences
• Expertise in data science, modeling, machine learning, and analytics. Experience successfully deriving insights from data, modeling, and simulation into actionable algorithms that drive business value. Expertise in big data technology infrastructure and environments coupled with the business process.
• Ability to communicate clearly, concisely, and convincingly with technical and non-technical audiences.
• Strong leadership skills and the ability to align cross-functional groups and influence business executives and stakeholders
• Deep knowledge of data and how to apply that data; business acumen to understand what needs to happen in order to support business objectives; technology skills to select the right tools and techniques to execute on objectives; communication skills to get the buy-in needed to get everyone else pulling in the same direction
• Be a result-driven individual; be highly creative, innovative, and analytical; be a strategic thinker; have an ability to work comfortably in a collaborative setting; be comfortable working with business top-leadership and executives; be highly organized; have an ability to work on multiple simultaneous projects and meet tight deadlines; have the ability to navigate times of uncertainty and stress; be a team-builder; be proactive and self-driven requiring minimal supervision; be open and welcoming to change

Additionally, The Ideal Candidate Will Possess The Following

• Knowledge of diabetes management
• Knowledge of diabetes products, business models, industry practices and the competitive landscape
• Knowledge of control engineering
• Knowledge of user-centric design
• Experience working in an agile environment

Education Requirements

• Degree in Computer Science, Data Science, Machine Learning, Statistics, or another related field. Advanced degree (Ph.D., MS) preferred. An equivalent combination of education and work experience is also acceptable for the position.