Data Scientist, Professional I

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:

This is a demand forecasting role on a team that builds and operates production forecasting platforms for retail and CPG customers. In a typical quarter you’ll design and implement a new component of the forecasting pipeline for an incoming customer’s data; diagnose and resolve a production performance regression; investigate a customer planner’s question about why an upcoming promotion’s forecasted lift looks low; write up the technical analysis in a way the customer can follow; and partner with engineering and customer-facing teams to deploy your changes safely

Minimum education:

College degree in engineering, computer science, data science, operations research, statistics, mathematics, quantitative sciences, or relevant work experience.

Minimum work experience:

1 years of experience in Data Science or Data Engineering with emphasis on the full lifecycle of demand forecasting or time-series modeling projects — including production deployment, monitoring, and ongoing model performance management.

Within that timeframe, experience is expected in: Python/PySpark, SQL, and relational or NoSQL databases, and cloud resource management.

Key skills and competencies

• Hands-on experience designing and operating production demand forecasting systems using statistical time-series methods (ARIMA, exponential smoothing) and regression-based approaches (log-linear regression, LASSO) for price elasticity and promotional lift modeling. Familiarity with hierarchical and weekly SKU-level forecasting at retail scale.
• Direct experience in retail or CPG demand forecasting, promotional planning, or supply-chain analytics — either as a vendor delivering forecasting platforms to retailers, or in-house on a retail/CPG demand planning team. Comfort interacting with merchant, replenishment, or supply-chain stakeholders to explain forecasting decisions.
• Track record across the full lifecycle of forecasting platforms — designing and building new components for incoming customers, evolving existing pipelines as customer needs change, diagnosing production issues, and explaining model behavior to customer planners and merchants.
• Proven experience building end-to-end production-grade data and ML pipelines using PySpark, Python (Pandas/NumPy), and SQL — including ingestion of customer transactional and master data, feature engineering for promotional and seasonal effects, model training and scoring at scale, and producing forecasts consumed by downstream merchandising and replenishment systems.
• Experience with forecast accuracy measurement (MAPE, WAPE, bias decomposition) and using accuracy diagnostics to drive iterative model improvements in production.
• Experience working with AWS, Azure, or GCP cloud environments at production scale.
• Experience with orchestration tools like Databricks, Airflow (or similar tools like Snowflake, Dagster, etc.).
• Experience working with Git (or similar code management repositories) as a collaboration tool.
• Excellent verbal and written communication skills, especially as it relates to technical communications. Ability to present technical analysis — including model behavior, forecast deviations, and recommended actions — to business stakeholders and customer planners.
• Demonstrated ability to learn new technologies quickly and independently.
• Ability to work independently with minimal supervision and achieve stretch goals in a very innovative and fast-paced environment.

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.