Oferta pracy

Commercial Digital Data Scientist

Pepsico Global Business ServicesO firmie

Rekrutacja zdalna

Rekrutacja zdalna

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Pepsico Global Business Services

Aleja Pokoju 18


PepsiCo products are enjoyed by consumers more than one billion times a day in more than 200 countries and territories around the world. PepsiCo generated more than $64 billion in net revenue in 2018, driven by a complementary food and beverage portfolio that includes Frito-Lay, Gatorade, Pepsi-Cola, Quaker and Tropicana. PepsiCo's product portfolio includes a wide range of enjoyable foods and beverages, including 22 brands that generate more than $1 billion each in estimated annual retail sales.

We’re on the look-out for a
Commercial Digital Data ScientistNumer ref.: 218172BR

Job Description

The retail landscape is changing at a rapid pace. The boundaries between online and offline have never been more intertwined. In an effort to accelerate the omnichannel transformation agenda, PepsiCo Europe will be investing in developing advanced digital sales solutions for our independent customers

As an innovative company, PepsiCo Europe decided to develop digital platforms and expand them across all of its business units. Additional digital tools & capabilities will be built in light of customers’ needs and PepsiCo’s growth aspirations in the future. We are looking now for a Commercial Digital Data Scientist who will take ownership of advanced analytics models, supporting commercial digital capabilities.

Main Purpose

  • Produce, manipulate, and interpret model outputs to facilitate use by local teams or local tools.

  • Support integration of model outputs into local business processes.

  • Identify and escalate opportunities to enhance and expand model functionality and applications.

  • Act as a lead point of contact with Sector and GBS Advanced Analytics teams.


  • Build & codify local approach: collaborate with sector stakeholders to co-create capabilities, tools & processes to drive efficiency, effectiveness & sufficiency.

  • Develop best-practices and scale lifting and shifting learnings across countries and categories

  • Maintenance of existing models

    • Periodic refresh of existing models across markets and brands

    • Periodic model validation to check the need for a rebuild

    • Guiding business with periodic updates

  • Formulate hypotheses, plan and execute statistical models for measurements/ROI analyses, share results with key leaders as well as drive meta-learnings

  • Ensuring Statistical robustness of the models and model reads

  • Ensure timely build and refresh of the models so that it can help in timely business decisions

  • Actively test data science concepts, and technologies that can be scaled across the portfolio

  • Partner with PepsiCo functional teams, agencies, and third parties to ensure acquiring, tagging, cataloging, and managing data periodically in structured format as needed for measurement statistical models

  • Create reusable modeling assets(codes, techniques, functions) to cut short refresh and model build time

  • Engage in R&D to try new modeling techniques to ensure faster and better answers to business problems


Key Skills/Experience Required
  • 2-3 years of hands-on data science, model building
  • High level of proficiency in either R or Python
  • Experience either in analytics consulting or internal analytics teams
  • Experience in translating a business problem into an analytics framework and vice versa
  • ‘Best in class’ data science capabilities, for instance, a degree in data science or maths.
  • Advanced knowledge of key data science techniques:
    • Combining data from multiple sources through APIs, Semantic Web, etc.
    • Data preparation and feature engineering
    • Supervised / Unsupervised learning
    • Collaborative Filtering
    • Location of Analytics & Intelligence
  • Hands-on knowledge of statistical modeling- well versed in techniques like regression, Bayesian, SEM, etc.
  • Hands-on with Machine learning concepts & skills – Regularization, Gradient-based optimization Hyper-parameter tuning, models like Random Forest
  • Able to translate complex concepts into clear stories for the business

Nice-to- have skills

  • Azure, VBA, SQL, MS Excel knowledge 
  • Familiarity with Scala, Java, or C++
  • Familiarity with query languages such as SQL or Hive 
  • Turkish Language

What we can offer

  • Employment contract
  • Competitive salary
  • Private healthcare
  • Life insurance
  • Multisport card

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