About The Role

Overview

At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs and solve their challenges.

Being part of Zebra Nation means you are seen, heard, valued, and respected. Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve.

You’ll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about—locally and globally.

Come make an impact every day at Zebra.

What We're Looking For

The Data Scientist Sr will have experience working across the full lifecycle of a Data Science project. The ideal candidate will demonstrate proficiency in the design, building, and optimization of data ingestion and data transformation pipelines; the design, enhancement and tuning of ML/AI models, the operationalization of resultant models; and communicating root cause analysis and model explainability to business stakeholders. The role will entail interfacing with various source systems, and proficiency in PySpark, SQL, Databricks, and related cloud resource management services. Prior experience with advanced analytics, ML/AI, and optimization solutions in the Retail/CPG domain is strongly preferred. A working knowledge of GenAI/LLMs and Agentic-AI in the context of workflow automation will be valuable but is not the primary requirement for this position. Responsibilities

Design, optimize , and maintain scalable ETL pipelines using PySpark and Databricks on cloud platforms ( Azure/GCP ).
Develop automated data validation process to proactively perform data quality checks.
Employ key Databricks modules ( DeltaL iveTables , Unity Catalog, MLFlow ) to facilitate creating , running experiments, automating , and scheduling jobs on Databricks.
Optim ize the allocation of cloud resources and Databricks DBUs to manage and control cloud and Databricks consumption cost.
Employ GitHub repositories to ensure that production code management best practices are being strictly adhered to .
Build and tune ML/AI and optimization model s , identify algorithmic performance improvement opportunities, and perform experiments to demonstrate incremental value delivered .
Have frequent conversations with Business Stakeholders to understand their requirements and concerns. E xplain data deficiencies, model performance/root cause analysis , and model output .
Follow best practices in Data Architecture, Coding, and Project Management operations.
Collaborate with cross-functional teams, such as Customers’ Stakeholders, Engagement Managers, Data Ops/Job Monitoring, Product Management & Software Engineering .
Expand the use of analytics, ML/AI, mathematical optimization, Gen -AI/LLMs and Agentic-AI in the context of Retail/CPG business use cases such as anomaly detection, demand forecasting, pric e elasticity modeling, promotions features & strategy simulation, product cannibalization and halo modeling , markdown optimization , product allocation, reorder/replenishment, size and pack optimization, workforce scheduling & task optimization

Qualifications

Job Requirements

Minimum Education:
Master’s degree in engineering, computer science, data science, operations research, statistics, mathematics , quantitative sciences or relevant work experience
Minimum Work Experience (years):
6 + years of experience in Data Science/Data Engineering with emphasis on the full lifecycle of Data Science-ML/AI project s .
Within that timeframe , experience is expected in: Python/ PySpark , SQL, and relational or NoSQL databases , and cloud resource management .
Key Skills and Competencies:
Experience working with AWS, Azure, or GCP cloud environments.
Experience implementing advanced analytics, ML/AI algorithms (such as : ,
S tatistical T ime S eries: Exponential Smoothing Models , S/ ARIMA ;
M achine L earning: Random Forests, Gradient Boosting Method s ;
Neural Networks : TiDE ( Google ) , DenseNet & Prophet ( FB-Meta ) ;
Foundational Time Series Models: TimesFM ( Google ) , Chronos ( AW S )
Mathematical (constrained linear , non-linear and network) optimization models
Proven e xperience building end-to-end production grade Data & ML/AI pipelines using PySpark , Python (Pandas/NumPy) and SQL .
Experience working with Git (or similar code management repositories) as a collaboration tool. production-grade
Experience with orchestration tools like Databricks, Airflow (or similar tools like Snowflake, Dagster , etc.) .
Understanding of Retail/CPG industry business challenges with an emphasis on Supply Chain, Pricing /Promotions/Markdowns, Inventory Allocation, Assortment Mix Planning, Size & Pack Optimization, Retail Shrink/Fraud & Anomaly Detection, and Workforce optimization applications are highly desirable.
Excellent verbal and written communication skills, especially as it relates to technical communications. Ability to present technical analysis to business stakeholders.
Demonstrated ability to learn new technologies quickly and independently , particularly as technology in this domain rapidly advances . In this context, a w orking knowledge of GenAI/LLMs, Agentic-AI and related frameworks ( e.g. LangChain ) will be a plus .
Ability to work independently with minimal supervision and achieve stretch goals in a highly innovative and a fast-paced environment.

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Benefits

We understand the importance of work-life balance and wellbeing, which is why we offer flexibility for our teams including: hybrid work, adaptable hours, Summer Flex Fridays, Focus Fridays, and an annual companywide well-being day to promote revitalization and success.

Job Posting Statement

To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you via @zebra.com email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department.

AI Technology Statement

Zebra Technologies leverages AI technology to evaluate job applications using objective, job-relevant criteria. This approach enhances efficiency and promotes fairness in the hiring process. However, every decision regarding interviews and hiring is made by our dedicated team, because we believe people make the best decisions about people. For more on how we use technology in hiring and how we process applicant data, see our Zebra Privacy Policy .