Offers “PepsiCo”

days ago PepsiCo

NRM Data Scientist

  • Internship
  • RUSSIA
  • Personal services

Job description

Auto req ID: 214401BR

Job Description

This role is responsible for working on developing trade promotion forecasting, pricing, optimization and other models for mayor markets. This role will involve creating, understanding and deploying Machine Learning models for PepsiCo, developed internally and in collaboration with Consultants, and work with the Core Team (PEP NRM, IT/CDO) to incorporate learnings into a sustainable, scalable product. These models will be deployed on PepsiCo’s platform in Microsoft Azure while supporting the use of standard PepsiCo toolsets and libraries.
This role will continue to develop machine learning and deep learning models while collaborating with the central team in creating best practice approaches to industrialize models, drive technical solutions in which to host models at scale and help in deploying these models. This role also needs to engage with market business process and data experts to better understand specific market data nuances and ways in which output of the models will be consumed (e.g. dashboards, integration with other systems, etc.).
This role will support the following activities:
·  Partner with consultant scientists working on the NRM Digital projects.
·  Partner with IT & CDO ML engineers to help extract Consultant models best practices and expand PepsiCo’s NRM digital product.
·  Partner with IT Data and ML engineers to ensure that proper data is prepared for model consumption.
·  Coordinate work activities with Business teams, other IT services and as required.
·  Hold team accountable for milestone deliverables to NRM and Business stakeholders.
·  Drive the use of the Platform toolset and to also focus on 'the art of the possible' demonstrations to the business as needed.
·  All statistical / ML / AI methods will be developed in a ‘product’ type nature with the ability to lift and shift to other PepsiCo BUs or more easily integrate with Enterprise First.
·  Requires strong communications with the Business, DS and DE Team and extended IT/ CDO teams.
·  Support large-scale experimentation and build data-driven models
·  Refine requirements that will be used to train and evolve deep learning models and algorithms.
·  Influence NRM product team through data-based recommendations.

Qualifications/Requirements

·  5+ years developing real-life (actually used in a business scenario) statistical modeling in industry tools with primary focus on Python development.
·  5+ years experience in AI/ML, Statistical techniques such as forecasting, various regression techniques, clustering, factor reduction, Machine Learning, Deep Learning with the ability to explain results
·  3+ years working in a team to deliver commercialized analytic solutions, not just stand alone.
·  Business story telling and communicating data insights in business consumable format
·  Highly Analytical, with solid critical thinking able to quickly connect technical and business ‘dots’
·  Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities
·  Experience with Agile methodology for team work and analytics ‘product’ creation.
·  Ability to identify optimization-related requirements and solution approach, in collaboration with external consultants. Experience with optimization software like Gurobi/Cplex is a huge plus .
Differentiating Competencies
·  Strong Business acumen and ability to communicate in business language
·  Translates complex technical solutions into business understanding
·  Creates solutions with the ability to continually prove accuracy and with a design goal of productization/ reusability.
·  Identifies and designs Advanced AI/ML Analytical solutions that start with significant ambiguity and will drive strong collaborative discussions with the business on problem scope, value sizing, factor reductions, variable importance and overall business usability.

Relocation Eligible: Not Applicable
Job Type: Regular