Looking for a new role that will be both challenging and rewarding, then continue reading to see if this position grabs your interests. The Manager of Seller Fees & Incentives Data and Analytics will drive data and analytics function for the pricing lever for our business - seller fees and incentives.
You'll sweep us off our feet if:
You're a strategic and structured problem-solver at heart.
You're organized, detail oriented, disciplined, and can manage multiple projects simultaneously.
You have strong communication skills and can translate complex data concepts and analyses into simple and easy to understand language.
You have strong exploratory data analysis skills, ability to make analytical, data driven recommendations and a track record of taking ownership.
You have proven experience in translating business requirements into innovative data solutions that drive growth and leveraging data to inform business strategy and process design.
You are curious and seek to understand business problems beyond the task or data.
You like building lasting partnerships, working cross-functionally, and tackling problems across a range of analytical topics.
You accept and thrive in constantly evolving, fast-paced, multi-dimensional environments.
You are curious, proactive, and comfortable working in unstructured set up.
You're stimulated by challenges and are ready to engage at Fortune 1 scale.
You'll make an impact by:
Building Solid Fees & Incentives Data Foundation for US Marketplace.
Build capabilities to store historical WMT seller fees and develop tools to scrape and store competitive fees data.
Build and pressure testing Incrementality models to assess fees incentives ROI.
Leverage incentives data to create data lake of fees incentives rules, spend data, ROI and KPIs.
Translating Data into Insights, Strategies, and Actions for X-functional Teams.
Conduct exploratory data analyses to generate insights and identify patterns in fees and incentives data.
Develop and implement causal and statistical analyses and models to determine drivers of incentives spend and ROI, predict outcomes, generate and communicate insights to inform/influence business decisions.
Distill large, complex data sources into recommendations for x-functional teams and leadership to understand and navigate easily.
Build dashboards to visualize incentives data and insights.
Supporting Business Case Creation for Incentive Programs
Engage w/ Business Leads, Seller Account Managers, and Program Managers to understand business needs and support design of fee-driven incentive programs aimed at driving target seller behavior and deliver business results.
Support x-functional partners to build business case (including financial model), define specific & trackable KPIs.
Building Data Tools to Support Incentives Management Process
Leverage world-class incentives data, models, and feedback tools to help build the WMT incentives experience for internal teams and sellers.
Support business teams by building centralized methodologies and data tools to streamline data pulling required for business case submission and incentive approval process.
Performing SWAT-team Analysis for Fees and Incentives Topics
Support Seller Fees and Incentives team with ad hoc fees and incentives analyses to inform strategic decisions and optimize incentives spend.
Partnering with Data Science Team on Recommendation Engines and Predictive Models
Work w/ Data Science team to build advanced analytics recommendations engines and predictive models required to enable incentives spend scaling for high ROI programs.
Pressure test logic behind models and validate model outputs to ensure recommendations are grounded in reality.
Collaborating with Product, Engineering on Fees Engine
Support Business Leads and Product Management team with integration of data signals into incentives engine to support new incentive launches and enhance incentives management process.
Liaise w/ Business/Product teams to align on tech roadmap to enable scale, flexibility, and effectiveness in management of our fees incentives spend.
Minimum Qualifications
Bachelor's degree in Statistics, Computer Science, Business, Economics, Finance, or related quantitative field.
2 years of experience in data analytics or related field role (e.g., advances analytics, data science, management consulting, investment banking, strategy and operations, or similar role).
Advanced SQL, Python/R, Google Big Query, and Google Cloud Platform.
Experience with statistical methods and advanced modelling techniques.
Experience working with and manipulating large data sets and writing basic SQL scripts.
Experience working cross-functionally.
Preferred Qualifications
MBA or master's degree in Statistics, Computer Science, Business, Economics, Finance, or related quantitative field.
4 years of experience in data analytics or related field role (e.g., management consulting, investment banking, strategy and operations, advances analytics, data science or similar role)
Experience manipulating large data sets, writing custom SQL/Python/R scripts, working w/ Google Big Query, and Google Cloud Platform.
Experience working with modern data visualization tools such as Looker and Tableau and communicating findings to an executive audience.
Experience in translating business requirements into innovative data solutions that drive growth and leveraging data to inform business strategy and process design.
Experience building and executing strategic business processes within a large organization including working with technology partners to deliver automated information solutions.
Strong exploratory data analysis skills and ability to make analytical, data driven recommendations based on insights from data.