Whole Foods Market
Revolutionizing the grocery landscape (again).
Austin, TX

Principal Data Scientist, Pricing at Whole Foods Market (Austin, TX)

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Provides leadership and oversight to the Data Science team. Provides functional oversight and ensures effective and business-focused aggregation, analysis, and interpretation of customer, transaction, product, and other relevant data. Oversees the analysis of customer, transaction, and product-related data to identify patterns and drivers through machine learning, data mining, and statistical models. Works with company leadership to ensure a widespread and mutual understanding of data-driven insights and their application to strategic, business, and tactical planning and marketing.


Provides leadership and oversight to team responsible for deploying machine learning and other advanced analytic approaches for testing, measurement and optimization of Whole Foods Market pricing. Oversees the engagement with cross-functional partners in Marketing, Merchandising and other Enterprise Analytic teams to drive programmatic process improvements and best-in-class pricing across Whole Foods Market. Monitors the grocery retail pricing space, providing thought leadership and

innovation to drive the evolution of pricing at Whole Foods Market.


  • Develop and implement ML based test, measurement and optimization solutions that will enable Merchants to make data driven pricing decisions which drive measurable improvements in business outcomes.
  • Develop empirically based recommendations for merchants and the Pricing team regarding item attribute premiums, volumetric discounts, rounding rules, laddering, KVI/KCI/ROS item classification and competitive price index targets.
  • Lead efforts to define capability requirements and transition plan for the next generation of WFM pricing system and process, collaborating with Pricing Strategic Planning, Pricing Coordination & Execution, Merch Ops, Tech, Marketing, Finance and other key business partners.
  • Collaborate with Merchandising, Marketing, and various Enterprise Analytic teams on strategic use of pricing data and analytics.
  • Collaborate with Merchandising, Marketing, and various Enterprise Analytic teams on strategic use of pricing data and analytics.
  • Translate and present complex analytical results into clear, concise, and actionable insights to all levels within the organization.
  • Drive the adoption of appropriate pricing science methodology and techniques to support pricing science within WFM. Helps gains merchant alignment on final pricing recommendations, collaborating with the Pricing Coordination & Execution team
  • Provides analysis to inform pricing strategy and rule recommendations, collaborating with Pricing Strategic Planning team
  • Serves as a key leader within the Pricing Science and Enterprise Analytics function.
  • Supports pricing reviews with merchants by providing guidance on the full pricing lifecycle of base, markdown and promotion pricing levers (in collaboration with Promotion Science).
  • Develops strong, credible relationships with senior leaders and executives, both inside and outside current areas of responsibility.
  • Keep up to date with latest developments in pricing science which encompasses Predictive Analytics and Machine Learning approaches to measurement and testing of pricing initiatives.
  • Maintain a thorough understanding of WFM pricing processes to effectively understand and analyze internal and external data.
  • Drive best practices and standards around the usage of data science tools (e.g. AWS, Spark, Hadoop, Spark, Jupyter Notebooks, Code repositories etc.)
  • Support the development and training of data scientist on the team.
  • Coordinate data scientist’s workload and partner across teams to ensure efficiency, accuracy and deliver work on-time.
  • Provide thought leadership on data science tools, systems and methodologies.


  • Working knowledge of advanced price optimization techniques which can achieve operational efficiency and financial objectives.
  • Proven ability to take complex business analyses and projects from concept to completion and make the results accessible and relevant to business users at all levels.
  • Ability to effectively present information and respond to questions in one-on-one and large group situations involving senior leadership and other teams in the organization.
  • Self-directed, innovative thinker with a strong attention to detail and commitment to consistently meeting timelines and operating from a sense of urgency.
  • Possesses strong customer service orientation – responsive, organized, strong communicator, sensitive to time urgency in relation to questions and business decisions, coordinates with others to develop solutions to merchant pricing related questions and issues. Defines, develops and implements initiatives to enhance customer service.
  • Strong understanding of mathematical and statistical concepts. Experience with utilizing advanced mathematical, statistical and data mining techniques to analyze data and construct solutions for complex business problems.
  • Advanced hands-on experience analyzing large, complex data sets using R, Python, Spark, Hadoop, Jupyter Notebooks, AWS, Java, Scala or any other analytical packages/tools/languages
  • Ability to review team’s coding for accuracy and improvement.
  • Comfortable with uncertainty: projects and assignments will change rapidly so must be flexible enough to accommodate changing priorities and timelines.
  • Excellent organization and time management skills. Ability to multi-task as well as communicate and reset priorities amidst incoming ad hoc requests with short deadlines.
  • Positive attitude, ability to work well under pressure and provide exceptional customer service.
  • Comfortable in a decentralized structure where results are based on cooperation with and influence of others.
  • Ability to work with partners who have a range of analytical skill sets.
  • Highly skilled at communication (written, verbal and listening), relationship building, influence/negotiation and team building
  • Work effectively with others on a team
  • Ability to maintain confidentiality

Education and Experience:

  • BA/BS degree in Statistics, Economics, Mathematics, Operations Research, or related quantitative field. Master’s degree preferred.
  • 6+ years of experience in advanced analytics or data science role, ideally in retail pricing
  • 2+ years leadership experience in analytics or data science

At Whole Foods Market, we provide a fair and equal employment opportunity for all Team Members and candidates regardless of race, color, religion, national origin, gender, pregnancy, sexual orientation, gender identity/expression, age, marital status, disability, or any other legally protected characteristic. Whole Foods Market hires and promotes individuals solely based on qualifications for the position to be filled and business needs.

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Where we are

Located in the heart of downtown Austin, we've been a mainstay in the Austin community since 1980.

Technology we use

  • Engineering
    • C#Languages
    • C++Languages
    • JavaLanguages
    • JavascriptLanguages
    • PythonLanguages
    • SqlLanguages
    • jQueryLibraries
    • ReactLibraries
    • ASP.NETFrameworks
    • Node.jsFrameworks
    • Microsoft SQL ServerDatabases
    • MySQLDatabases
    • OracleDatabases

What are Whole Foods Market Perks + Benefits

Volunteer in local community
Partners with Nonprofits
On top of working with personal nonprofits, Team Members can work with and contribute to our three main nonprofits -- Whole Planet Foundation, Whole Cities Foundation, and Whole Kids Foundation.
Friends outside of work
Eat lunch together
Intracompany committees
Join committees ranging from our hiring committee, Inclusion Task Force, and more.
Daily sync
Open door policy
Team owned deliverables
Team based strategic planning
Group brainstorming sessions
Open office floor plan
Health Insurance & Wellness Benefits
Flexible Spending Account (FSA)
Disability Insurance
Dental Benefits
Vision Benefits
Health Insurance Benefits
Life Insurance
Wellness Programs
Onsite Gym
Mental Health Benefits
Retirement & Stock Options Benefits
Company Equity
Performance Bonus
Child Care & Parental Leave Benefits
Generous Parental Leave
Flexible Work Schedule
Family Medical Leave
Return-to-work program post parental leave
Vacation & Time Off Benefits
Generous PTO
Paid Holidays
Paid Sick Days
Perks & Discounts
Casual Dress
Commuter Benefits
Company Outings
Game Room
Some Meals Provided
Happy Hours
Pet Friendly
Relocation Assistance
Professional Development Benefits
Diversity Program
Lunch and learns
Cross functional training encouraged
Promote from within
Mentorship program
Time allotted for learning
Online course subscriptions available

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