Associate Manager, Data Science

Key Skills

A/B Testing, Analytical and Problem solving, Azure, Big Data Technology, Cloud computing, Data science techniques, Databricks, Deep Learning, Machine learning techniques, Mathematical modeling, Pandas, PowerBI, Python Programming, PyTorch, Scikit-learn, Snowflake, SQL, Statistical modeling, TensorFlow, XGBoost

Job Description

Overview

PepsiCo is a global food and beverage leader with a product portfolio including 22 brands that generate more than $1 billion each in annual retail sales along with a billion smiles. Our main businesses – Pepsi, Frito-Lay, Quaker and Gatorade – make hundreds of enjoyable foods and beverages that are loved throughout the world.

At PepsiCo, you get the best of both worlds: an entrepreneur’s mindset plus reach and resources. Our collaborative culture and worldwide presence generate a stream of new opportunities to define the future and propel your life’s work. Bring your unique perspective. Bring curiosity. Bring ingenuity, and drive. We’ll give you a platform to be daring on a global scale.

About the Job:

If you are passionate about problem solving and want to fuel growth, come join the PepsiCo Customer Team for Walmart Inc., which includes Walmart US and Sam’s Club. The Associate Manager Advanced Analytics for PepsiCo’s Walmart Customer Team will be crucial in leading data science and analytics practice, leveraging internal data as well as Walmart’s new Luminate data platform to accelerate growth.

In this role, you will lead data science and visualization initiatives for omnichannel performance across the entire beverages and foods portfolio for a significant portion of PepsiCo’s business in North America, reporting into the Director of Advanced Analytics. The Associate manager of Data Science would be someone who thrives at the intersection of data science, technology and business understanding to drive source to shelf supply chain analytics and bring an understanding of economics to inform pricing and net revenue management analytics to drive omnichannel revenue growth and improve share of market. You are someone who loves to look for the best solution instead of being satisfied with the status quo.

You would be communicating the results to key commercial team members in sales, supply chain, marketing, eCommerce and Insights teams. It will be critical to derive meaningful insights and translate sophisticated analysis or into actionable and clearly expressed conclusions that will empower the business to take meaningful actions.

What our team does:

• Applied Data Science and Visualization to predict and understand cross channel Walmart performance
• Perform statistical analysis across diverse datasets to drive and measure performance
• Build machine learning systems to understand the cross-channel Walmart performance
• Work with PepsiCo’s strategic partners to expand their technical capabilities, thereby creating a more robust data environment
• Solve commercial problems from headquarters all the way down to the field

Responsibilities

• Hands on mining of large data sets and development of supervised and unsupervised models/algorithms to uncover trends, patterns, and insights
• Establish standards for writing clean, organized machine learning code to streamline machine learning workflow within the team
• Provide critical thought leadership to enhance organizational capabilities by utilizing a variety of data sets; work with business stakeholders to identify and execute on opportunities for enhancement
• Partner with other analytics teams within PepsiCo to foster enhanced analytical capabilities globally
• Have a curious mindset and explore and learn new technologies that might be relevant to the role
• Be and expert in Python, SQL, machine learning algorithms, and know about data integration, modeling and be well-versed in versed in good UI design
• Explore and implement ways to enhance data quality and reliability
• Collaborate with data scientists and architects as needed

Qualifications

• Bachelor’s degree (B.S./B.A.) in computer science, information systems, informatics, statistics, economics, engineering, or another quantitative field or equivalent from a college or university with IT focused specialization
• 4-6 years of relevant work experience
• PhD. a plus but not required
• At least 4 years of software development and machine learning experience in a business environment
• Experience delivering forecasting and/or pricing analytics projects
• Ability to direct data engineers to build widely consumable and reusable data models
• Expert in mathematical models underlying data science methods
• Demonstrated ability to communicate with both business and technical audiences effectively and concisely
• 2-4+ years of experience leading/building advanced analytics and big data solutions
• Knowledge of the data science art (feature engineering, modeling, AI capabilities, optimizers) and related technologies (cloud computing, open-source analytical capabilities)
• Highly collaborative and demonstrated experience working well in matrix team environment
• Demonstrated ability to drive innovative solutions using data science, feature engineering and machine learning
• Demonstrated ability to effectively communicate with all levels of the organization
• Demonstrated flexibility to manage resources to plan, including effectively handling spikes in demand
• CPG industry experience is a plus

Skills, Abilities,Knowledge:

• Data Science – Hands on expert in building machine learning models – supervised and unsupervised models like clustering, regression, classification, anomaly detection, time series, etc
• Programming Skills – Expertise in statistical programming languages like Python, database query languages like SQL, and machine learning packages like scikit-learn, pandas, xgboost etc
• Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, A/B testing etc
• Cloud (Azure) – Experience in Databricks/PySpark and distributed databases like Snowflake preferred
• Data Visualization tools and/or toolkits like Power BI, Streamlit etc
• Some familiarity with Deep learning frameworks like PyTorch, TensorFlow