Director of Advanced Analytics at Alex Lee

Alex Lee

5d•Remote

About The Position

We are seeking a Director of Advanced Analytics at Alex Lee to serve as our founding advanced analytics leader — building the enterprise analytics function from the ground up across our portfolio of grocery retail and wholesale operating companies. This is a high-impact, hands-on leadership role for a professional who is equally comfortable translating business strategy into analytical solutions and presenting findings to the C-suite.This person will own the full analytics lifecycle end-to-end, with an initial focus on customer (guest) analytics and AI-driven use cases, expanding over time to merchandising, supply chain, operations, finance, marketing, and real estate. As the function matures, there is a clear path to build and lead a team. Remote role but must be within driving distance to Hickory, NC for on-site meetings as needed

Requirements

8+ years of progressive experience in advanced analytics or data science, with demonstrated business impact.
Bachelor’s degree in a quantitative field (Data Science, Advanced Analytics, Statistics, Mathematics, Computer Science, Economics, or Engineering); Master’s strongly preferred.
Proven ability to partner with business leaders, frame problems, and translate analytical results into strategic decisions.
Experience operating at both a senior leadership and hands-on practitioner level across the full analytics lifecycle.
Expert proficiency in Python; strong SQL and experience with large-scale data platforms (Snowflake, Databricks, BigQuery, or Redshift).
Strong command of statistical and ML methods: regression, forecasting, classification, clustering, and predictive modeling.
Hands-on experience with ML frameworks (scikit-learn, XGBoost, TensorFlow, PyTorch) and AI applications including generative AI and NLP.
Proficiency with data visualization tools and ability to build executive-ready dashboards and presentations.
Familiarity with MLOps, model deployment, and cloud-based analytics environments; Microsoft Fabric or Azure ML experience preferred.
Strong understanding of experimental design, A/B testing, and causal inference.
Experience taking models and insights from experimentation into production systems. This includes working with Data Engineering on deployment, monitoring model performance, retraining processes, and working with technology teams to integrate analytics into live environments.
Exceptional communicator — able to present complex analytical topics clearly to both technical and non-technical audiences at all levels.
Ability to influence without authority and drive adoption of analytics across a matrixed organization.
Strong business acumen with the ability to connect analytical work to tangible business and financial outcomes.
Self-directed, entrepreneurial mindset — comfortable building from scratch in ambiguous environments.
High intellectual curiosity, strategic thinking, and the executive presence to represent analytics at the leadership table.

Nice To Haves

Prior experience in retail, grocery, CPG, wholesale, or consumer-facing industry strongly preferred.
Microsoft Fabric or Azure ML experience preferred.

Responsibilities

Partner with senior leaders across all operating companies to identify, prioritize, and frame high-value analytics opportunities.
Develop and communicate a multi-year advanced analytics roadmap aligned to business priorities.
Champion data-driven decision making across the enterprise, building organizational confidence and capability.
Represent analytics at the executive level with clear, compelling narratives that enable confident decisions.
Execute the full analytics workflow: data discovery, exploratory analysis, modeling, validation, and communication of results.
Build statistical models, machine learning solutions, and AI-powered tools that address specific business problems.
Develop scalable, reproducible analytical frameworks that serve as the foundation for future team growth.
Collaborate with Data Engineering and IT to ensure access to high-quality data assets and appropriate infrastructure.
Lead development of advanced guest analytics: segmentation, lifetime value modeling, churn prediction, and personalization.
Apply AI and machine learning to surface actionable insights from guest behavior data across digital and in-store touchpoints.
Expand analytics capabilities over time to merchandising, supply chain, operations, real estate, and finance.
Evaluate and implement emerging AI technologies — including generative AI and large language models — applicable to our business context.
Develop proof-of-concept projects and pilots that demonstrate AI’s business value and build the case for broader investment.
Own developed AI models to ensure integrity over time.