Data Science Sr Scientist

PepsiCo•Plano, TX

2d•$80,200 - $134,250•Onsite

About The Position

PepsiCo Data & Analytics Overview: With data deeply embedded in our DNA, PepsiCo Data & Analytics transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo’s leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise. The Data Science Pillar in D+A is our core organization that Data Scientist and ML Engineers report to in the broader D+A Organization. Members of the Data Science Pillar will lead collaboration in the larger DS community in PepsiCo. These members are the talent powering the development and support of DS components within the life cycle of all D+A Products. They also may support pre-engagement feasibility activities as requested and validated by the prioritization framework of D+A. Position Overview: Your role will be to be part of an established team in Plano, to create and support global digital developments for PepsiCo within our Consumer Activation space. As a Data Science Senior Analyst, you will play a pivotal role in leveraging advanced analytics and machine learning to deliver impactful solutions across critical business topics relating to our consumers. You will be part of a collaborative interdisciplinary team around data, where you will be responsible for building deployable statistical/machine learning models, beginning from the discovery phase through implementation. You’ll collaborate closely with process owners, product managers, and end-users to ensure your developments are aligned with business priorities and drive measurable outcomes. You will be an internal ambassador of the team’s culture around data and analytics fostering a culture of innovation, analytics, and collaboration. You will provide stewardship to colleagues in the areas that you are a specialist or you are specializing contributing to the team’s growth and success in data and analytics.

Requirements

3+ years’ experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems.
3+ years’ experience in developing business problem related statistical/ML modeling with primary focus on Python development.
2+ years’ experience working with modern cloud platforms to power ML solutions.
2+ years working in a product focused team to deliver production level analytic solutions.
Business storytelling and communicating data insights in business consumable format. Fluent in one Visualization tool.
Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities
Experience with Agile methodology for team work and product creation.
Experience in Reinforcement Learning is a must.
Experience with Pyspark is a must.
Experience with SQL is a must.
Fluent in git with an understanding of Jenkins or Docker a plus.
Experience with NLP is a plus.
Experience with LLM is a plus.
Experience with working with FAIR data is a plus.
Experience with Responsible AI is a plus.
Experience with distributed machine learning is a plus

Nice To Haves

Fluent in git with an understanding of Jenkins or Docker a plus.
Experience with NLP is a plus.
Experience with LLM is a plus.
Experience with working with FAIR data is a plus.
Experience with Responsible AI is a plus.
Experience with distributed machine learning is a plus

Responsibilities

Contributing member in a digital project.
Present your findings in a business friendly manner to our stakeholders.
Build machine learning models with minimal oversight.
Act as a subject matter expert in our digital project to other teams.
Be a contributor in innovation activities.
Partner with product managers in proving feedback on story points and tickets.
Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption.
Contribute with work activities that involve Business teams, other IT services and as required.
Drive the use of the Platform toolset and to also focus on 'the art of the possible' demonstrations to the business as needed.
Communicate with business stakeholders in the process of service design, training and knowledge transfer.
Support large-scale experimentation and build data-driven models.
Set KPIs and metrics to evaluate analytics solution given a particular use case.
Refine requirements into modelling problems.
Influence product teams through data-based recommendations.
Research in state-of-the-art methodologies.
Create documentation for learnings and knowledge transfer.
Support in creation reusable packages or libraries.