Analyst III - RGM Data Science
The Kraft Heinz CompanyMatch Score
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Protocol Intelligence
Data-driven signals on your job's competitivenessMid-level role, metro location, and common toolset create moderate applicant competition.
Strong CPG POS and forecasting experience requirement makes cross-industry transferability low.
Role demands domain-specific CPG POS experience plus ML and SQL skills, so screening will be strict.
Job Description
Structured overview of role & requirementsAbout This Role
Transform, clean, and analyze CPG POS data using Excel, Python, SQL to enable reliable reporting and answer time-sensitive business questions.
Apply supervised machine learning techniques (Regression, Decision Trees) for forecasting, driver analysis, and performance evaluation in the CPG context.
Translate data insights into clear business narratives and recommendations for both technical and non-technical stakeholders.
Minimum Requirements
Strong proficiency in Advance Excel, Python, SQL; Power BI is good to have.
Experience working with CPG POS data, including sales, pricing, promotions, and distribution metrics.
Knowledge of supervised machine learning techniques such as Regression and Decision Trees with model evaluation experience.
Work Experience Required: Preferred 4-6 years in Data Science focused on Regression and Forecasting models in CPG or related analytics.
Ideal Candidate Profile
Experienced in end-to-end data wrangling and analytics workflows across tools (Excel, Python, SQL).
Demonstrated ability to deliver actionable insights under tight timelines, geared towards supporting CPG business decisions.
Domain expertise in CPG data analytics, particularly price/promo impact on sales and assortment optimization.