Head Of Data Science

The Kraft Heinz Company Chicago , IL 60602

Posted 2 weeks ago

Kraft Heinz, The Company

As one of the world's largest food and beverage companies, we are proud to spark joy around mealtimes with a global portfolio of more than 200 brands. Some are iconic master brands like Heinz, Kraft and Planters. Others are fast growing new sensations that defy status quo like DEVOUR and Primal Kitchen. No matter the brand, we are united under one vision To Be the Best Food Company, Growing a Better World. Bringing this vision to life are our 36,000+ teammates around the world, making food people love.

Together, we help provide meals to those in need through our global partnership and commitment with Rise Against Hunger. And we also stand committed to sustainability, and the health of our planet and its people.

Every day, we are transforming the food industry with bold thinking and unprecedented results. If you're passionate like us -- and ready to create the future, build on a storied legacy, and participate as a conscientious global citizen -- there's one thing to do join us.

Our Culture of Ownership, Meritocracy and Collaboration

We're not afraid to think differently. Embrace new ideas. Dream big. It all comes down to the way we empower our people to own their work. It's true Our employees are our competitive advantage.

As part of the Kraft Heinz family you're supported to grow and achieve. You're recognized and rewarded for outstanding performance at every level. You're given the opportunity to leave your mark and build legacies. But you won't do it alone. This is where our values and teamwork thrives and collaborative spirit fuels every day.

Job Description

The Head of Data Science is the US Finance lead responsible for leading our data science team. This role reports directly to the Sr. Director of Data and Analytics.

We are looking for a motivated leader that has solid industrial research experience and management skills. The data science team is responsible for quantitative data analysis, building models and prototypes for Kraft Heinz, and building state-of-the-art algorithms to forecast. This team plays a significant role in the innovation pipeline from business needs, research work, prototyping/simulation, to implementation by working closely with a variety of colleagues in engineering, product management, and senior leadership.

Technical Responsibilities:

  • Mastery of Python

  • Interact with engineering, operations and business teams to develop an understanding and domain knowledge of operational processes, system structures, and business requirements.

  • Apply domain knowledge and business judgment to identify opportunities and quantify impact

  • Come up with strategies with quantitative modeling and mathematical optimization to enhance existing and develop new forecasting algorithms and strategies on workforce planning

  • Apply advanced mathematical and heuristic optimization techniques to design scalable, optimal or near-optimal solutions

  • Create prototypes to test devised solutions and leverage in-house simulation platforms for high-fidelity validation

  • Work closely with engineers to integrate the prototypes into production systems using standard software development tools and methodologies

  • Leverage policy evaluation platform to track the actual performance of a devised solution in production systems, identify areas with potential for improvement and work with internal teams to improve the solution with new features

Leadership Responsibilities:

  • Mentor research and applied scientist team members for their career development and growth

  • Be data-driven, details driven and frequently audit the quality and scalability of solutions during the research process

  • Be efficient in aligning research direction to business requirement and make the right judgment on research project prioritization

  • Effectively advocate technical solutions to business stakeholders, engineering teams, as well as executive level decision makers

  • Excel in evaluating the skill sets of candidates to make successful hiring decisions to meet business needs

Minimum Qualifications

  • Masters in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)

  • 6+ years of experience working in data science

  • 3+ years of experience managing Machine Learning Scientists, Data Scientists, Research Scientists, Applied Scientists, and/or Economists

  • 2+ Years of cloud experience (preferably Azure)

  • Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, NLP, deep learning, recommendation systems, dialogue systems, information retrieval

  • Skilled with Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language

  • Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives

  • Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes

  • Experience hiring and leading experienced scientists as well as a successful record of developing junior members to a successful career track

  • Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts.

  • Project management experience for working on cross-functional projects

  • Proven achievements of developing and managing a long-term research vision and portfolio of research initiatives, with algorithms and models that have been successfully integrated in production systems

Preferred Qualifications

  • A PhD in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)

  • 5+ years of experience managing Machine Learning Scientists, Data Scientists, Research Scientists, Applied Scientists, and/or Economists

  • 3+ years of CPG experience

  • 3+ years of Azure experience

  • Professional experience in software development (software design and development life cycle)

  • Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives

  • Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes

Location(s)

Chicago/Aon Center

Equal Opportunity Employer-minorities/females/veterans/individuals with disabilities/sexual orientation/gender identity


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Head Of Data Science

The Kraft Heinz Company