Data Science Manager

• Managing core delivery teams of Kaizen and non-Kaizen (clients, third parties) resources that possess business, technology, and data science skill sets
• Managing multiple work streams from acquisition and planning through successful delivery
• Solving business problems through excellent decision-making and innovative, strategic ideas
• Implementing solutions in either client or Kaizen environments

• Understand business context of analytics solutions: Current state, problem, goals/objectives and their business value, obstacles, and impacted client constituents
• Lead teams (core delivery team, client teams, or both) in translating business problems faced by clients into analytics solution requirements; building mathematical algorithms and models that provide an analytical framework for analyzing and solving business problems; and for developing working knowledge of new analytics models and solution techniques
• Provide client-specific thought leadership for defining modeling and measurement techniques and utilizing mathematics, statistical methods, engineering methods, operational mathematical techniques to estimate benefits from using analytical models
• Lead teams of data scientists, analysts, and software engineers in performing analysis (applying multi-variable, complex statistical analysis on large data sets to gain useful insights into the data, detect trends and outliers/invalid data conditions that exist in data sets) and delivering analytics solutions that are of high quality and scaled to client needs in terms of sophistication
• Effectively present analysis, models, results, and insights at the right level of detail to client teams (executive-level to user-level) and Kaizen teams
• Facilitate a critical communications role by interacting with analytics solution users (business domain), core delivery team members (project domain), and development personnel (technical domain)
• Efficiently navigate and lead core delivery team and client (both business and technical domains) through ambiguity of business process, organizational change, and detailed requirements
• Provide internal Kaizen teams with thought leadership for brainstorming, developing, delivering, and testing service-oriented software or subscription offerings for targeted clients / industry verticals
• Support sales and business development activities for both existing and new clients
• Contribute to Kaizen’s knowledge capital by drafting articles and presenting at industry conferences

• Education and Experience:
  • Ph.D. in Operations Research, Data Science, Business Analytics, Industrial Engineering, Econometrics, Computer Science, or other applied mathematical discipline, with at least 5 years of relevant professional experience

• • Master’s degree in Operations Research, Data Science, Business Analytics, Industrial Engineering, Econometrics, Computer Science, or other applied mathematical discipline, with at least 7 years of relevant professional experience
• Expertise in two or more of the following areas: math programming, probability, statistics, forecasting, machine learning, artificial intelligence, or other heuristics
• Effective communication (written and verbal); Excellent presentation skills; Mindset of “own it all the way through solution”
• Minimum 3 years of firsthand experience in two or more of the following: R, SAS, Python, CPLEX/Gurobi, MATLAB
• Functional Skills: Ability to structure and analyze large data sets; Highly proficient in Microsoft Office applications; Good working knowledge of Data Visualization tools (Tableau and Power BI are preferred)
• Project Management: Ability to manage projects using SDLC (Software Development Life Cycle), PMI, and Agile methodologies
• Ability to travel as dictated by business needs

• Possess industry experience in Automotive, Media & Entertainment, Communications, or Consumer Goods
• Have experience with data mining and business reporting
• Be passionate about analytics and helping companies deliver value through analytics

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