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 a Decision Science Analyst - eCommerce, this role will focus on linking clickstream and event-level data with completed transactional data to understand how different parts of the site and app drive sales, margin, and profitability. The Decision Science Analyst will connect pre-purchase digital behavior (navigation paths, feature usage, funnel progression) with post-purchase outcomes (orders, revenue, discounts, and profit) to evaluate performance at a granular level. 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. Do you have a: 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? We are looking for: - 2+ years of relevant experience, preferably in retail / other consumer-facing industry - Experience working with clickstream or event-based data - E-Commerce experience highly preferred - Experience in statistical programming languages (R, Python, SQL) and familiarity with big data ecosystems (Databricks, Spark, etc.), relational DBs, SQL, business intelligence and visualization tools (Tableau or MicroStrategy, etc.) What is the work? Design & Development / Analytics: - Evaluate digital experiences based on revenue and profit impact, not just engagement or conversion metrics - Identify which site and app surfaces drive the highest-value transactions, informing prioritization of product and UX investments. - Measure the true financial impact of experiments, releases, and feature changes, including downstream effects on average order value, discounting, and margin. - Support trade-off decisions between growth, conversion, and profitability by providing clear, data-backed insight. - Create a shared source of truth between product, analytics, and finance by aligning behavioral data with transactional results - Mines / validates / cleanses data - Works across several data platforms (e.g., clickstream, web analytics, transactional data, unaggregated customer data) - Applies experience, knowledge, intuition to dig for insights to share through enterprise tools (e.g., Tableau, MicroStrategy) - Asks questions to identify deeper reasoning behind business questions - Translates / tests / connects data findings into actionable business insights - Provides ad hoc analysis upon request Advising: - 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 What is your background? - A related degree or comparable formal training, certification, or work experience - 2+ 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 Do you have what it takes to be a fit as a Decision Science Analyst at H-E-B? - Working knowledge of typical data science techniques (e.g., classification, regression, and optimization) - Working 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 MicroStrategy, 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 Can you... - Thrive in a fast-paced retail environment with rapidly shifting market-driven priorities 08-2021