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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Proficient in analyzing retail demand through advanced forecasting techniques, utilizing Python and SQL for data manipulation and model development. Demonstrates expertise in statistical analysis, machine learning fundamentals, and data validation to enhance forecasting accuracy and decision-making processes.
Highest-signal resume keywords
Python ProgrammingSQL ProficiencyForecasting FundamentalsData Analysis and VisualizationMachine Learning Fundamentals
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Statistics and ProbabilityForecast Error MetricsData ValidationClean Code WritingExperiment DesignModel TuningImage Processing BasicsClustering TechniquesAnomaly DetectionProbabilistic Modeling
Soft Skills
Clear Written CommunicationClear Spoken Communication
Tools & Technologies
DatabricksOracle RetailGitGitHubAI Coding Assistants
Industry Keywords
Retail Demand AnalysisSupply Chain KnowledgeCPG KnowledgeZero-Inflated ModelsOptimization Tools
Tech Stack
Tools & technologiesNumpyOraclePandasPySparkPythonSQL
About the role
Key responsibilities & impact- Analyze and segment intermittent retail demand using sales frequency, zero-sales patterns, and volumes
- Define dedicated forecasting processes from data preparation through forecast output
- Build probabilistic forecasting models predicting sales timing and size
- Benchmark forecasts against Oracle system forecasts using appropriate accuracy metrics
- Characterize products by velocity, seasonality, volatility, and lifecycle
- Build Databricks tuning pipelines and parameter matrices for Oracle Retail AIF settings
- Validate forecasting parameters in Oracle test environments and compare accuracy
- Design and implement decision-tree diagnostic engines for forecast root-cause analysis
- Detect and report seasonality anomalies, inflated demand, eligibility errors, and outlier-handling gaps
- Build and test production-grade diagnostic code and documentation
- Assess product attributes and image similarity to identify look-alike historical items
- Develop new-item forecasting and matching pipelines and assess scalability
- Present results and recommendations
Requirements
What you’ll need- Python, including pandas and NumPy where applicable
- SQL
- Statistics and probability, including Markov Chains, distributions, and estimation
- Forecasting fundamentals and error metrics such as MAE, bias, and MASE
- Data analysis, reporting, and visualization
- Clear written and spoken English
- Machine learning fundamentals, similarity, and clustering for Topic 4
- Basics of image processing or computer vision for Topic 4
- Data validation and quality checking for Topic 3
- Ability to write clean, maintainable code for Topic 3
- Experiment design and model tuning basics for Topic 2
- Applicants should submit their resume in English
- Nice-to-have skills include intermittent demand methods, Databricks/PySpark, Oracle Retail or enterprise forecasting software, retail/CPG or supply chain knowledge, probabilistic or zero-inflated models, clustering, optimization tools, anomaly detection, dashboards, vector search, pretrained image embeddings, Git/GitHub, and AI coding assistants
Benefits
Comp & perks- Learn and have fun in a passionate data science team
- Opportunity to work with AI development tools including Claude, Cursor, and Databricks
- Work on projects with results feeding into real client implementations
- Production-ready development experience and exposure to Oracle environments
- Final presentation of results and recommendations
- Internship experience in retail, science, and scalable technologies