Manager, Data Science

over-deliver on internal stakeholders' needs for analysis and insight. Position has open access to all forms of enterprise data and scope of work covers basic to advanced numerical methods including modeling and simulation. Regression, classification, optimization, and machine learning all potentially play a role in this function.

JOB DESCRIPTION

• Advanced numerical methods: develop and implement predictive models, segmentation methods, optimization algorithms, machine learning.

• Know and understand statistical limitations of data; keen understanding of analysis of variance.

• Perform work and analysis for a 'multi-channel' environment applying analytics to online and offline environments.

• Research and develop new forms of analytic methods applicable to relevant business objectives.

• Duties and responsibilities include but are not limited to business insights including all relevant behavior analysis, product and promotion testing, real estate, concessions (merchandise) performance and allocation.

• People leadership and influence skills with ability to communicate at all levels of organization, introduce new ideas, sell complex concepts, train staff.

• Produce compiled data, reports and 'visualized' results for all levels of the organization.

Required

• MSc/PhD in Statistics, Math, Operation Research or related degree with 6+ years experience
• 3+ years hands-on experience and proficiency with:
  • Computational Programming with R, Python
  • Statistical Modeling
• Evidence of leadership capability. Ability to influence others.
• Knowledge of Classification Systems, Recommendation Systems, Predictive Modeling
• Objective evidence of advanced SQL capability, querying large, complex datasets using relational databases
• Proven analytical capability with intermediate to advanced knowledge of statistics as it relates to all aspects of data set analysis including error, experimental design
• Strong data interpretation, visualization and presentation skills
• Ability to explain statistical approaches/models used, rationale/merits of different approaches, results and interpretation to team members
• Able to work effectively in a collaborative team environment
• Familiarity with machine learning
• Intellectually curious / quick thinker
• Willingness / ability to take ownership as technical lead of a project and lead others