Description

You will apply quantitative and qualitative analysis to synthesize trends into actionable insights and business predictions.

This role is on-site.

Responsibilities

• Build and maintain predictive forecasting models using machine learning techniques including regression, classification, clustering, and neural networks.
• Execute customer segmentation, product mix, and promotion mix analysis using multivariate models and Turf Analysis.
• Source, combine, and synthesize large datasets from various sources to perform data mining and wrangling.
• Develop effective data visualizations to allow users to interact with forecasting models.
• Present data stories and strategic action plans to stakeholders to drive sales across product categories.

Required Skills

• 10+ years of professional experience.
• Advanced Python skills including Pandas, Scikit-Learn, TensorFlow, and Keras.
• Proficiency in Machine Learning methods: Clustering, k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests, and Time series Forecasting.
• Expertise in Alteryx, R, and Advanced Analytics.
• Strong applied statistical skills including statistical tests, distributions, regression, and maximum likelihood estimators.
• Experience with Data Visualization tools such as Power BI and Tableau.
• Proven ability in data mining and handling data imperfections through wrangling.
• Bachelor's degree in Business, Analytics, Data Science, Statistics, Mathematics, or a related field.

Preferred Skills

• Master's Degree in a quantitative field.
• 4+ years of specific experience in Retail Performance analytics and data modelling.

Key Skills

Education

Bachelor's degree