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About the Role
In this role, you are responsible for the design, development, programming methods, processes and systems to consolidate and analyze unstructured, diverse "big data" sources to generate actionable insights and solutions for businesses across the company. You will support the team in building data and analytics capabilities to enhance the analytical platform, partnering with Global Technology Solutions, Product, and business teams to advance retail forecasting across the organization.What You'll Do
Design, develop, and deploy enterprise planning, or decision-support systems, forecasting in retail, consumer, marketplace, or supply-chain domains that support multi-horizon planning and scenario evaluation.Â
Expertise in Time series forecasting: hierarchical/aggregated forecasting, reconciliation concepts, seasonality, and multi-horizon evaluation.
Develop software programs, algorithms and automated processes that cleanse, integrate and evaluate large data sets from multiple disparate sources
Manipulate large amounts of data across a diverse set of subject areas, collaborating with other data scientists and data engineers to prepare data pipelines for various modeling protocols
Build, validate, and maintain AI (Machine Learning (ML) /Deep learning) models, diagnose and optimize performance and develop statistical models and analysis for ad hoc business focused analysis
Create measurement strategies for accuracy, bias, stability, and business outcomes; run back tests and controlled experiments where feasible.
Advanced proficiency in Python, Spark, and common scripting languages for E2E pipeline Advanced proficiency using SQL for efficient manipulation of large datasets in on prem and cloud distributed computing environments, such as Azure, GCP environments
Communicate meaningful, actionable insights from large data and metadata sources to stakeholders
Collaborate with others in key initiatives and their implementation
Responsible for planning, budget and end results; set policies and strategic direction for area/team
Who You Are
Experience with ML and classical predictive techniques such as logistic regression, decision trees, non linear regressions, ANN/CNN, boosted trees, SVM, Tensorflow, visualization packages, and a track record for creating business impact with these methods
Experience in econometric demand modeling and prescriptive analytics, including elasticity, promo lift, Bayesian methods, and optimization-based decision modeling.
Ability to work both at a detailed level as well as to summarize findings and extrapolate knowledge to make strong recommendations for change
Ability to collaborate with cross functional teams and influence product and analytics roadmap, with a demonstrated proficiency in relationship building
Evaluate sometimes complex situations using multiple sources of information (internal and external sources)
Able to filter, prioritize, analyze, and validate potentially complex In-depth understanding of concepts and procedures within own subject area and understanding of procedures and concepts in other areas
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