Leverage advanced analytics, machine learning, and data visualization techniques to deliver actionable insights that support strategic business decisions for Sam's Club Merchandising Analytics team.
Requirements
- Proven expertise in predictive analytics, machine learning algorithms, and advanced statistical methods to solve complex business problems.
- Proficiency in Python programming and data visualization tools such as Matplotlib, Plotly, Tableau, or PowerBI.
- Strong knowledge of data strategy, data quality standards, and data governance principles within large-scale data ecosystems.
- Experience in exploratory data analysis, feature engineering, and model assessment using techniques like ROC curve and hypothesis testing.
- Ability to deploy, monitor, and scale machine learning models in production environments with MLOps best practices.
- Proficiency in Databricks, GCP, Big Query, and Google ADK.
- Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch)
Responsibilities
- Identify and source relevant data from multiple business domains and distributed data stores to support analytics initiatives.
- Develop, validate, and tune predictive models using advanced statistical and machine learning techniques to solve complex business problems.
- Create clear and impactful data visualizations to communicate insights and model outcomes to stakeholders.
- Deploy and monitor models in production, ensuring scalability and performance alignment with defined metrics.
- Design and implement advanced recommendation and assortment models tailored to merchant behaviors, with a focus on quality and pricing optimization across diverse product categories.
- Develop sophisticated anomaly detection and clustering models that uncover patterns, inflection points, and root causes—delivering actionable insights quickly and accurately for specific categories.
- Build isolation matrices and causal inference frameworks to drive data-driven decision-making and uncover hidden drivers of business performance.
Other
- Immigration sponsorship is not available for this role.
- Collaborate with cross-functional teams to translate business needs into data-driven solutions and actionable recommendations.
- Mentor team members on analytical methods, coding best practices, and data science workflows.
- Bridge business and analytics by applying a consultative mindset to data science problems—evaluate whether a problem is worth solving, assess downstream impacts, and ensure solutions align with broader business goals.
- Will be a hands-on technical leader, quickly identifying the right algorithms and approaches to solve complex problems and delivering high-impact solutions with speed and precision.
