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Fuels Data Scientist II

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Job ID 2024-264046
Address 3200 Hackberry Rd, Irving, Texas, 75063, US
Store-ID Store Support Center Store-Type US Non-Store

Who we are

With more than 13,000 stores in the U.S. and 84,000 stores globally, it is no wonder 7-Eleven, Inc. has been named an iconic brand. In addition to 7-Eleven stores, 7-Eleven, Inc. also operates and franchises Speedway, Stripes, Laredo Taco Company and Raise the Roost locations.

Since inventing the convenience industry in 1927, 7-Eleven has built a rich 96-year history filled with beloved products like Slurpee, Big Gulp and Big Bite, and fan-favorite holidays like Slurpee Day and Bring Your Own Cup Day.

Now, 7-Eleven is on a mission to contemporize the brand and redefine convenience – and we need your help.

▶ About This Opportunity

As a Fuel Pricing Data Scientist, you will uncover key insights on how customers engage with 7-Eleven. Part of a rapidly growing team, you will apply data science methods and analytics to real business situations across retail fuel pricing. This role will enable fuel pricing decision making by developing key insights into our customer engagement and translating these insights into large scale predictive modelling and analytics solutions.

Design, develop, and implements different ML frameworks/solutions and data pipelines to solve business problems/opportunities related to fuel pricing.
Adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action
- Create and build predictive models and analytic systems aimed at solving fuel pricing problem/opportunity statements.
- Automates data pipelines and develops/utilizes different libraries for statistical algorithms that measure and predict KPI's related to fuel pricing and customer behavior/buying preferences.
- Create actionable insight reports supported with data visualizations, and support A/B testing methodologies.
- Utilize AI to predict customer behavior.

-  Price Optimization, Anomaly detection, customer retention, clustering, time series, sales forecasting, discount analysis, inventory and cost analysis, market basket and affinity analysis.


  • Strong Python skills with experience in TensorFlow or PyTorch or other ML Libraries.
  • Proven experience with RNNs and time series forecasting.
  • Previous application of ML Models in a retail or other industry setting.
  • Advanced degree in Data Science, Statistics, or related field.
  • Strong analytical and problem-solving skills.
  • Experience with big data tools (e.g., Spark, Databricks)
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