Zebra Technologies, or simply Zebra, is an information technology and services company that provides a performance edge to individuals and companies on the fron
Senior Data Scientist
Location
Worldwide
Posted
81 days ago
Salary
0
Seniority
Senior
Job Description
Senior Data Scientist
Zebra Technologies
Role Description 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 a 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 a 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. - 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 (DeltaLake, Unity Catalog, MLFlow) to facilitate creating and scheduling jobs on Databricks. - Optimize the allocation of cloud resources to manage and control cloud cost. - Employ GitHub code management repositories and ensure that best practices are being implemented. - Build and tune ML/AI and optimization models, identify improvement opportunities, and perform experiments to demonstrate incremental value. - Have frequent conversations with Business Stakeholders to understand their requirements and concerns. Explain data deficiencies, model performance/root cause analysis, and model explainability. - 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 - Price 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 - Minimum Education: Master’s degree in engineering, computer science, data science, operations research, statistics, mathematics, quantitative sciences or relevant work experience. - Minimum Work Experience: 4+ years of experience in Data Science/Data Engineering with emphasis on the full lifecycle of Data Science-ML/AI projects. - Experience in Python/PySpark, SQL, and relational or NoSQL databases, and cloud resource management. - Experience working with AWS, Azure, or GCP cloud environments. - Experience implementing advanced analytics, ML/AI algorithms (such as statistical time series: ESMs, ARIMA; machine learning: Random Forests, GBMs; Neural Networks: TiDE & DenseNet, foundational models) and mathematical (constrained linear/non-linear and network) optimization models. - Proven experience 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. - Experience with orchestration tools like Databricks, Airflow (or similar tools like Snowflake, Dagster, etc.). - Working knowledge of GenAI/LLMs, Agentic-AI and related frameworks (e.g. LangChain) will be a plus. - Understanding of Retail/CPG industry business challenges with an emphasis on Supply Chain, Pricing and Workforce optimization applications is preferred. - 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. - Ability to work independently with minimal supervision and achieve stretch goals in a very innovative and fast-paced environment. Requirements - Licenses/Certifications: N/A - Equivalencies: Relevant work experience may be substituted for a degree. Benefits - 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.
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Product Operations Analyst – Product Analytics
DoiT InternationalDoiT develops the technology and expertise needed to solve both essential and complex cloud challenges.
• Support and evolve the framework and systems that turn product behavior into trusted, actionable signals: • Partner with Engineering to define and maintain event taxonomy, tracking standards, and instrumentation quality • Build and maintain scalable, self-service dashboards for product teams • Help establish and document clear metric definitions as a shared source of truth. • Contribute to improving how and what we measure as the product evolves. • Leverage AI to repeatedly unlock insights and recommendations from these signals • Strengthen the product analytics ecosystem and data models that power decision-making. • Work within our product analytics stack (e.g., Mixpanel, Segment, Looker) to ensure accurate and accessible reporting. • Build and maintain dbt models for core product entities and behaviors. • Contribute to a clean, usable metric layer for business stakeholders. • Help structure and analyze Voice of the Customer inputs (e.g., support, churn, NPS, sales feedback, customer interviews) • Support data quality through testing, monitoring, documentation, and automation • Deploy the best AI tooling available to make our data a differentiator • Translate product usage and customer signals into clear, actionable insights. • Deliver recurring product analytics reporting (adoption, engagement, retention) • Contribute to analytics readouts to business stakeholders and executives with clear findings and recommendations • Perform analyses that connect product behavior to revenue and retention outcomes • Support automated reporting and AI-assisted workflows while maintaining metric integrity • Strive to make insights and reporting automated and self-service, heavily assisted through best practices with emerging AI techniques



