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  • Analytics & Insights Manager

    • J.Crew
    • New York, NY, USA
    • Feb 13, 2020
    Full-time Analytics Data Integration Data Management Data Modeling Data Visualization Predictive Analytics R SQL Strategy Tableau

    Job Description

    The Insights & Analytics team is responsible for analyzing vast amounts of data to better understand and predict customer behavior that in turn informs business decisions and improves J.Crew Group customers’ experiences. Our team has a broad mandate, handling customer analysis across the entire organization and informing marketing, merchandising, planning, stores/field, budgeting and other financial decisions.

    The Manager position is responsible for designing an appropriate methodology, accessing and analyzing large amounts of data, and synthesizing findings into insights in customer behavior. The work takes the form of strategic ad hoc projects, as well as more routine reporting to measure the effectiveness of various tactics and tests.

    Responsibilities include:

    • Regularly liaise with the marketing, loyalty, merchandising, and stores teams to understand their business needs and provide the right analyses/insights based on their key strategies and issues
    • Field ad hoc requests for customer analysis, acting as an analytical thought partner to the business stakeholder, and assigning the appropriate analytical approach
    • Conduct advanced customer analyses and arrive at compelling data conclusions, including but not limited to cross-shop, customer profiles and KPIs, and studies into customer loyalty, acquisition and retention trends
    • Translate data findings/trends into actionable insights to better understand complex shopping behavior and present analytical findings in easy-to-understand presentations, making clear recommendations based on deep insights into the data
    • Own, design, develop and distribute customer reports and dashboards that clearly track the effectiveness of strategies underway
    • Build predictive models to improve profitability, growth, retention, customer lifetime value, and other key performance indicators for our business stakeholders
    • Implement formal modeling processes from end-to-end including data gathering, data profiling, numerical model building, calibration, cross-validation, and launching in production
    • Advise on experimental designs to ensure new business strategies are tested appropriately and without bias; assist stakeholders in parsing results, arriving at conclusions and advising on next steps, when needed
    • Act as a subject matter expert on best practices in retail customer analysis
    • Work closely with vendors as needed to ensure integrity of data and analyses being provided
    • Liaise with our customer database provider as needed to ensure data is processed correctly and recommend any changes or updates to support the growing business needs

    The ideal candidate:

    • Has excellent familiarity with analyzing transactional customer data
    • Is analytical and curious, especially about how numbers can define company strategy
    • Is an excellent oral and written communicator who can clearly tell stories based on insights into the data
    • Understands the retail industry and the analyses common in the trade
    • Has advanced project management skills and efficiently manages tasks to completion
    • Has some degree of modeling experience or familiarity with CLV, churn, propensity, and multi-touch attribution models
    • Is extremely detail oriented
    • Has an entrepreneurial mindset and is comfortable with change and ambiguity
    • Is eager to continually improve his/her analytical and technical skills
    • Has a positive, can-do attitude and wants to be part of a critical team

    Education & Experience Requirements:

    • Master’s degree preferred in a quantitative field
    • At least 5 years’ previous work experience in retail / e-commerce
    • Superior research, statistical, analytical, processing and mathematical skills with ability to structure and conduct analyses
    • Strong proficiency in R, SQL and/or Python, Tableau and Microsoft Office Suite
    • Working knowledge of AWS toolkit, including S3, Athena, Glue, and Sagemaker
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