Advanced Data Scientist

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 .