Data Scientist

Are you a data scientist ready to work on enterprise AI/ML initiatives in a collaborative environment? Want to build impactful data science solutions on a best-in-class tech stack and strong data foundation? Then read on.

With over 2,900 stores across 19 states, Casey’s is the 3rd largest convenience store chain and 5th largest pizza chain in the United States. Known for our legendary made from scratch pizza and small-town charm, we’re a brand rooted in community and convenience.

Casey’s is seeking a Data Scientist to contribute to the advancement of enterprise data science initiatives aligned with the company’s strategic priorities and designed to enable data-driven decision making. As part of our centralized Data & Analytics team, you’ll collaborate with a skilled group of data scientists, analysts, engineers, and product owners to build and deploy scalable AI/ML solutions using a best-in-class tech stack and a robust data foundation.

Responsibilities

• Collaborate with business stakeholders, product owners, data and platform engineers, and various IT functional areas to develop end-to-end data science initiatives.
• Research, select, and apply the best analytical approach(es) (optimization, prediction, segmentation, simulation, etc.) and techniques (statistical analysis, machine learning, etc.) to solve the problem at hand.
• Translate complex analytical findings into clear, actionable insights for both technical and non-technical audiences.
• Partner with the Data Governance team to document solutions and implement automated model performance monitoring and reporting.
• Follow ML/DevOps best practices including version control, unit testing, peer review, and change management.
  
  

Compensation

Starting pay range:‏‏‎ ‎$101,700 - $139,800.‏‏‎ Actual pay may vary based on Casey’s assessment of the candidate's knowledge, skills, abilities (KSAs), related experience, education, and qualifications. Other factors impacting pay include local prevailing wages and internal equity. This position is eligible for an annual cash bonus based on company performance. Our full salary range for this role does extend beyond the hiring range listed, allowing team members the opportunity to continue to grow within the company.

What you can expect when you join the Casey's Team:

• A transformative culture putting service first and taking pride in caring for our guests, our communities, and each other.
• Opportunities to use cutting edge technologies and enterprise-wide collaboration to enable our strategy and drive world class service.
• We're here for families! Great benefits including choices in medical plans, dental, vision, life insurance, employee stock purchase program, charitable giving programs, parental leave and an onsite Child Development Center.
• Competitive pay, 401k company match up to 6%, vacation & sick time, paid holidays, volunteer time, and an onsite cafeteria.
• Dress for your day dress code, jeans are welcomed!
• The opportunity to work for a big company that has not lost our small company feel. Our senior leadership team is engaged, involved and accessible!
  
  

What are you waiting for? Come be a part of a company that is growing, transforming and is here for good!

Casey’s is headquartered in Ankeny Iowa, a suburb of Des Moines. Ankeny and the Des Moines Metro consistently rank among the best places to live in the U.S. thanks to affordable big-city perks and small-town warmth that make it ideal for young professionals and families alike. Whether you’re into biking trails, live music, craft breweries, golf, or quiet family friendly neighborhoods, you’ll find your place here.

Requirements

• Bachelors degree in a quantitative field (e.g.: Statistics, Operations Research, Industrial Engineering, Computer Science etc.) or equivalent work-related experience is required.
• At least three years of industry experience in a quantitative field with relevant research experience is required.
• Proficient in programming languages (Python, R), advanced SQL, and parallel computing techniques.
• Hands-on experience and deep understanding of common machine learning algorithms and statistical concepts like hypothesis testing, supervised & unsupervised learning etc.
• Proficient with ML packages like scikitlearn, TensorFlow, PySpark etc. technologies, ensuring their effective adoption within the team and products.
• Experience in deploying ML models in a production cloud environment using MLOps tools like Kubernetes, Airflow etc.
• Experience in data visualization software like R Shiny, Tableau, etc.
• Experience in owning and delivering models end-to-end.