ABOUT US
We build tools for 100+ brands and retailers in the e-commerce space that help them offer free two-day shipping, same-day delivery, and product expansion into new marketplaces -- keeping them several steps ahead of the curve in a rapidly changing industry.
We are a purpose and culture driven organization that prides ourselves on connectivity, equality, diversity and inclusion. We are committed to our people as a service-oriented company as our people are at the heart of everything we do.
We are Headquartered in Chicago, with offices in New York, Conshohocken, PA (Philly area), and Krakow, Poland and we operate as a subsidiary of FedEx Services.
ABOUT THE ROLE
ShopRunner’s SaaS products support online shoppers, retailers, and payment partners to improve shopping and shipping experiences. Every week, we track more than a billion interactions with shoppers across our network of merchants. Our analytics team uses this data to help make decisions about the effectiveness of our products.
As a product data analyst, you will leverage your skills in SQL, data engineering, and product planning to help us launch and measure our products. You will analyze consumer interaction data, manage A/B tests end-to-end. And you’ll build data pipelines, dashboards, and presentations to help our product, engineering, and account teams know what works and what we should build next.
This role reports to an Analytics Manager and works day-to-day as part of a large, cross-functional team. This person can be located in either Chicago or near Conshohocken, PA. Unfortunately, visa sponsorship is not being offered for this role.
WHAT YOU'LL DO
- Partner with product, engineering, and account teams to ensure that we are tracking the right data to fully measure effectiveness.
- Help build data pipelines (using dashboarding and ETL tools) to summarize raw data into useful datasets and dashboards, in order to simplify and scale our analysis.
- Define and document requirements for tracking user touchpoints with ShopRunner products.
- Contribute to ongoing and programmatic QA of data sources.
- Contribute to other analysts’ growth by sharing your skills and processes.
WHAT WE'RE LOOKING FOR
Required:
- 3+ years of data analyst experience, with responsibility for initiating, executing, and presenting projects for cross-functional teams.
- BS (or equivalent experience) in a technical field like Computer Science, Engineering, Mathematics, Statistics, or Marketing Analytics.
- Fluent with complex SQL queries on millions of rows (joins, subqueries, window functions).
- Experience with data visualization tools, like Looker, Tableau, or Power BI (we use Looker).
- Willingness to programmatically clean messy datasets (managing duplicate records and parsing Strings, JSON, or XML).
- Experience creating self-service dashboard suites
- Experience collaborating with product, engineering, and design teams
- End-to-end experience in measurement including the design of relevant KPIs, implementation of any required tracking elements, and report out on collected metrics.
- Confidence to share the limitations of your analysis when the data isn’t perfect.
- Advanced Excel proficiency (for example, you should be comfortable with pivot tables and lookups to summarize results).
Preferred:
- Proficient understanding of how event-level data is tracked, and their potential quality issues. Some examples of this would include event logs, sign-in data, creative rendering, or hit-level tracking with Google Analytics, Adobe Analytics, Snowplow Analytics, or Amplitude.
- Experience writing user stories and documentation for engineering teams.
- Experience working with e-commerce data.
- Experience with reproducible data analysis using Python or R.
- Basic understanding of prediction and personalization algorithms (e.g. purchase and churn propensity models, product recommendations). Note that this role will not build production models, but it will help if you understand how those models generally operate in connection to CRM and testing initiatives.
- Experience setting up processes to monitor datasets for anomalies.
We want you to bring your whole human self to work every single day. We accept you for who you are and consider everyone on an equal opportunity basis without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.