About the role

Senior Manager, Data Science at Grainger developing insights on customer experience through analytics and data science applications. Leading projects and managing a team to influence digital strategy.

Responsibilities

Inform digital strategy, website development and digital technology investments through analytics and data science applications.
Build statistical and machine learning models to uncover insights about digital customer experience.
Apply techniques such as clustering, classification, regression, natural language processing and time series modeling.
Leverage big data from multiple sources to build custom datasets, then visualize patterns, identify trends, and perform feature engineering / variable selection for further analysis.
Partner with a variety of business stakeholders to analyze opportunities and trends.
Lead the process of translating business problems into analytic projects, returning with powerful insights.
Manage a variety of projects concurrently.
Generate project ideas through business observations and interactions with business partners.
Communicate findings to audiences at all levels, including senior leadership.
Tell powerful data stories to make insights clear, influencing company strategy.
Manage a team of experienced data scientists and analysts to deliver insightful analytics and data science projects.
Provide coaching and mentorship to grow technical, analytic, and business skills within the team.
Function as a subject-matter expert on the analysis of big data. End-to-end expertise required, including dataset building/cleaning/transformation, analysis/model-building, and the presentation of actionable results.

Masters’ or graduate degree in a quantitative field required (mathematics, statistics, engineering, data science, analytics, operations research, economics, etc.) or equivalent work experience.
8+ years’ analytics/data science experience with strong business acumen, preferably with an understanding of online customer behavior in the retail industry. B2B experience is a plus.
Deep knowledge/proficiency in coding for data science and analytics applications (Python or R preferred).
Deep experience and expertise in statistical modeling and machine learning in-industry (regression, classification, clustering, natural language processing, time-series modeling).
Knowledge of database design and logic (e.g. Teradata, Snowflake), with demonstrable ability to build complex queries in SQL.
Proven record of using analytics to solve business problems by developing an analytical approach, identifying necessary data sources, executing the analysis, and tying it to actionable business decisions.
Broad business perspective with a strategic mindset and exceptional problem-solving skill.
Demonstrated thought leadership and intellectual curiosity.
Ability to influence decisions without authority.
2+ years’ experience as a people leader.
Excellent written and verbal communication skills, with an emphasis is compelling data storytelling.
Preferred experience in retail or B2B industries.
Preferred experience with digital commerce and web analytics tools such as Adobe Analytics or Google Analytics.

Medical, dental, vision, and life insurance plans with coverage starting on day one of employment and 6 free sessions each year with a licensed therapist to support your emotional wellbeing.
18 paid time off (PTO) days annually for full-time employees (accrual prorated based on employment start date) and 6 company holidays per year.
6% company contribution to a 401(k) Retirement Savings Plan each pay period, no employee contribution required.
Employee discounts, tuition reimbursement, student loan refinancing and free access to financial counseling, education, and tools.
Maternity support programs, nursing benefits, and up to 14 weeks paid leave for birth parents and up to 4 weeks paid leave for non-birth parents.