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Data Analyst

Data | Los Angeles, CA | Full Time

Job Description

Shopkick, the leading multi-chain shopper rewards app, is looking for a Data Analyst who will provide insights to our most important clients and Senior Management; develop understanding about how users engage with our App; and bring an analytical perspective to teams across the company.

 

We are actively seeking candidates who combine both the baseline technical skills required (see below) with strong “soft” abilities, including communication, influence, presentation, and prioritization.  This role will provide the right candidate with an unusually broad level of influence at Shopkick and exceptionally strong opportunities for growth.  

 

While we don’t use a formal “office” for any day-to-day work, we do benefit from being in the same room from time-to-time (post-Covid).  For that reason, we can only consider applicants already in or moving to Southern California at this time.

 

The Data Analyst will be responsible for:

  • Developing dashboards and reporting to support revenue teams as needed
  • Attending “live” meetings / VCs with sales teams, clients, and Marketing to represent Shopkick from an Analytics perspective
  • Using SQL, Python, Excel, and/or other BI tools to answer ad-hoc questions about client campaign performance.
  • Creating custom analysis of the Shopkick user base to understand how different categories and different types of Shopkick marketing vehicles influence consumers
  • Constructing and overseeing A/B/* experiments as part of Shopkick’s “test-and-learn” culture
  • Creating benchmarks and other aggregate insights that would be of interest to key clients, the press, and other external partners
  • Creating, measuring, and documenting KPIs that will drive focus across the business
  • Automating, maintaining, and improving all levels of client-facing reporting

 

Preferred Qualifications

 

  • Bachelor’s Degree or higher in a preferably-quantitative field (Math, Computer Science, Engineering, Data Analysis, etc.).  All programs of study considered for strong candidates who can show analytical ability.  Career switchers are welcome to apply, but please be prepared to demonstrate the skills required.
  • HARD REQUIREMENT:  Ability to extract data from databases by writing SQL, from scratch, including table joins, subqueries, and very basic window functions (rank, row_number, etc.).  You’ll be given “Notepad / TextEdit” and need to write some basic code to demonstrate this ability.  If you can’t do this, study up and please reapply later.  
  • Understanding of data visualization best-practices and experience in at least one tool through which that understanding can be expressed (Excel, Tableau, Python / matplotlib or other visualization libraries, etc.)
  • Experience with one or more data visualization / dashboarding tools, esp. Sisense / Tableau / PowerBI / etc. is helpful.
  • Ability to construct intermediate level Python code to assist with data cleaning, transformation, analysis, or visualization.  Use of python packages that allow creation of Office files (Excel, Powerpoint).
  • Ability to translate analytical results to a data-supported story; excellent written and oral communication skills
  • Self-learner, self-starter, high degree of intellectual curiousity; ability to thrive in fast-paced startup-y situation where problems are not always well-defined
  • Interest in digital advertising; understanding of advertising principles
  • 2+ Years of experience in a role where you can explain why your experience is relevant to the Data Analyst role at Shopkick

 

A Plus If You:

  • Have experience with Google BigQuery or other columnar data store (Vertica, etc.) or “big data” technologies
  • Have experience with JIRA/Confluence
  • Have created, run, and analyzed studies of marketing incrementality/lift
  • Have a Master’s Degree in a related field
  • Have experience with common 3rd party event-based analytics packages, such as Google Analytics, Amplitude, or Mixpanel
  • Have experience with advertising campaign analysis
  • Have experience with app user analytics
  • Have comfort with statistical analysis (i.e. can prove that differences in outcomes are statistically significant at a target level)
  • Can explain how “programmatic” advertising or Marketing Mix Modeling works; can discuss how to use first party data to make marketing more effective

Have Stephen Few, Cole Nussbaumer Knaflic, or Edward Tufte on your bookshelf


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