Assoc Decision Science Analyst - Wellness Reporting Analyst

Responsibilities

H-E-B is a 115-year-old grocery retailer, and we're a leading innovator in technology. Recently, we've been investing in our customers' digital experiences, using the best available technologies to deliver modern engagement, reliability, and scalability to meet their needs.

As an Associate Decision Science Analyst, you'll extract, explore, validate, and cleanse data using advanced coding techniques. You'll design and apply analytical and statistical models to segment, describe, and understand our customers and their purchasing habits and proclivities. You'll serve as a strategic thought Partner, providing perspective and recommendations to solve business challenges.

Once you're eligible, you'll become an Owner in the company, so we're looking for commitment, hard work, and focus on quality and Customer service. 'Partner-owned' means our most important resources—People—drive the innovation, growth, and success that make H-E-B The Greatest Omnichannel Retailing Company.

• HEART FOR PEOPLE… ability to work in a cross-functional, team-driven environment?
• HEAD FOR BUSINESS… experience in analytical and statistical modeling?
• PASSION FOR RESULTS… drive to turn data into actionable business recommendations?

• 0+ years of relevant experience, preferably in retail / other consumer-facing industry

• Using coding techniques (predominately SQL and Python), aggregates billions of data records to measure customer behavior changes in multiple dimensions (e.g., customer count and value, frequency of purchase, average purchase size, ROI)
• Mines / validates / cleanses data
• Works across several data platforms (e.g., clickstream, web analytics, transactional data, unaggregated customer data)
• Applies advanced analytical and statistical models to segment / understand our customer (e.g., k-means clustering, a/b testing)
• Applies experience, knowledge, intuition to dig for insights to share through enterprise tools (e.g., Tableau, Micro Strategy)
• Asks questions to identify deeper reasoning behind business questions
• Translates / tests / connects data findings into actionable business insights
• Provides customer insights and in-depth analytics on marketing initiatives (e.g., pre- / post-campaign)
• Develops / deploys experiments and data science models to measure customer loyalty, habits, tendencies, affinities, and propensities to reliably predict behavior and prescribe initiatives, strategies, tactics
• Provides ad hoc analysis upon request

• Serves as a strategic thought Partner / team member of assigned team; provides perspective on business challenges
• Serves as the data-expert in cross-functional groups to optimize H-E-B marketing investments and assortment decisions
• Provides day-to-day broad visibility into customer learnings and impact through ongoing performance dashboards / metrics
• Summarizes for / shares insights with business stakeholders, informally and in formal presentations
• Aligns with executive level stakeholders on prioritizing initiatives

• A related degree or comparable formal training, certification, or work experience
• 0+ years of relevant experience, preferably in retail / other consumer-facing industry
• Expertise in business domain
• Experience in statistical programming languages (R, Python, SQL)
• Experience in relational databases such as Teradata or Oracle and big data platforms
• Experience in data extraction, cleansing, validating, and curating

• Working knowledge of typical data science techniques (e.g., classification, regression, and optimization)
• Basic understanding of data exploration, applying analytical tools, and how to advise business stakeholders
• Familiarity with big data ecosystems (Databricks, Spark, etc.), relational DBs, SQL, business intelligence, and visualization tools (Tableau or Micro Strategy, etc.)
• Strong research and analytical skills
• Strong critical and lateral thinking skills
• Verbal / written communication and presentation skills
• Ability to turn data into actionable recommendations (vs. just reporting data)
• Ability to solve ambiguous, unstructured problems
• Ability to present / explain deliverables to non-technical stakeholders
• Ability to work within a cross-functional, team-driven structure

• Thrive in a fast-paced retail environment with rapidly shifting market-driven priorities

08-2021