Principal Supervisor - Data Science

Leads team that develops analytics strategies, identifies effective performance metrics, and recommends Business Intelligence (BI) technologies and applications. Provides oversight to analytical professionals on developing and implementing Business Intelligence (BI), Artificial Intelligence (AI) and Machine Learning (ML) projects. Advises senior leadership and enterprise stakeholders using sound analyses and data-driven insights. Span of control: Leads team of individual contributors.

• Oversees team of analysts and data scientists in the application of data science methods to identify business opportunities, predict performance outcomes and provide tactical and strategic recommendations
• Translates business and analytics strategies into multiple short-term and long-term projects, and ensures end-to-end execution of projects
• Supports scientific, measurable, and fact-driven approaches by adding statistical rigor to business recommendations
• Implements new, industry-leading statistical, mathematical, machine learning or other methodologies for modeling or analyses
• Discovers insights from Big Data to help shape or meet specific business needs and goals
• Identifies and evaluates technologies and provides strategic input to advance the organization's analytics capabilities
• Utilizes business expertise to translate goals into data-based deliverables, such as predictive models, pattern detection analysis or optimization algorithms and methods
• Ensures the accomplishment of the following core supervisory/management functions for a given group(s) within a business unit: planning, organizing, directing the performance of on-going activities and/or special/ad hoc assignments, staffing (employee selections, training, coaching and performance management, time entry), coordinating, reporting and budgeting
• Leads the continuous improvement commitment and efforts for team, including designing processes, establishing quality and quantity standards and metrics, collecting, refining, adapting, and communicating best practices, sharing knowledge, and developing staff in a systematic fashion; uses process design outcomes to solve problems
  

This is a dual-track base requirement job; education and experience requirements can be satisfied through one of the following two options:

• Bachelor's degree in quantitative field (e.g., Statistics, Computer Science, Information System, Engineering, Mathematics, Physics, Data Science, Industrial/Organizational Psychology and Econometrics, etc.) or Business Administration, and 7 years of experience working in a data analytical, computer programming, or engineering function, inclusive of two years of experience leading analytical projects; OR
• Master's degree in quantitative field (e.g., Statistics, Computer Science, Information System, Engineering, Mathematics, Physics, Data Science, Industrial/Organizational Psychology and Econometrics, etc.) or Business Administration, and 5 years of experience working in a data analytical, computer programming, or engineering function, inclusive of two years of experience leading analytical projects
  

Preferred

• Experience in quantitative analysis, query design, data visualization, statistical analysis, and predictive analytics

Other Requirements

• Proficient in quantitative analytics (e.g., data mining, regression analysis, hypothesis testing, A/B testing, machine learning modeling, including multivariate statistical analysis, natural language processing, unsupervised and supervised learning, deep learning, predictive modeling, and model optimization in production)
• Intermediate- to advanced-level knowledge and skills in data modeling, data structure, and the application of complex SQL queries with data from multiple sources, including a Big Data platform (e.g., Hadoop, AWS, Azure)
• Proficient in programming skills such as SQL, C/C++/C#, Java, R, Python, PHP, or SAS
• Ability to develop models in a Big Data cloud environment and deploy models in production
• Intermediate level skills and experience with data mining and statistical analysis using analytical packages / tools (e.g., R, SAS, SPSS, Stata, MATLAB, Minitab, etc.)
• Intermediate- to advanced-level skills and experience in articulating business questions, pulling data from relational databases (e.g., SAP Business Warehouse (BW), ORACLE, SQL SERVER) and using advanced excel and statistical tools (e.g., Minitab, Alteryx, Advanced Excel with VBA, R, SAS, SPSS, Stata, MATLAB, etc.), and determining the appropriate analytical approach to conduct in-depth analysis to support decision making
• Adept with multiple business intelligence tools and platforms (e.g., SAP Business Objects, Microsoft Power BI, Microsoft Azure, AI, and machine learning tools)
• Ability to lead analytical data projects across functional teams, including coaching and feedback of other team members on analytic approaches
• Excellent communication skills, including ability to interact with and influence decision-making by non-analytical business audiences
  

Incumbents may engage in all or some combination of the activities and accountabilities and utilize a variety of the competencies cited in this description depending upon the organization and role to which they are assigned. This description is intended to describe the general nature and level of work performed by incumbents in this job. It is not intended as an all-inclusive list of accountabilities or responsibilities, nor is it intended to limit the rights of supervisors or management representatives to assign, direct and control the work of employees under their supervision.