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.

• Designs systems that utilize data-oriented programming languages and visualization software to explore, analyze, and interpret large volumes of data in various forms and solve complex business problems • Defines data science initiatives by utilizing data mining, data modeling, natural language processing, and machine learning techniques to extract data from multiple sources and deliver predictive models that inform solutions • Designs and develops data solutions that meet client requirements and organizational quality standards by leveraging industry-leading tools, technologies, and best practices to profile and translate data • Applies data science expertise and machine learning knowledge to improve patient care capabilities, optimize healthcare operations, and drive evidence-based decision-making • Develops and implements analytical frameworks, key metrics, and performance dashboards to monitor, measure, and evaluate healthcare quality, efficiency, and performance • Collaborates with stakeholders across the organization, including executives, clinicians, Information Technology (IT) professionals, and business analysts, to understand their needs and provide data-driven solutions • Delivers presentations and consultative services to existing and prospective constituents on data analytics results and solutions • Improves professional data science knowledge by staying up to date on innovative data analysis techniques, visualization tools and software, and object-oriented programming languages • Helps establish and implement programs that ensure departmental adherence to all applicable data governance policies and procedures by educating team members on data science best practices

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 121 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com. Senior Data Science Manager - Ads Marketplace Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business. The Ads Marketplace DS team sits at the intersection of economics, machine learning, and human behavior. We are looking for a results-oriented and strategically minded Data Science Leader to work with our Ads Marketplace teams ensuring that every ad served provides value to the advertiser, maintains the integrity of the user experience, and optimizes the long-term health of our ecosystem. You will lead a team of high-caliber data scientists to partner with Product, Engineering, and Sales to build a world-class, transparent, and efficient marketplace. If helping Reddit’s advertising business reach the next level excites you, then you’ve found the right place. We’re a company with one of the highest employee/user ratios in the industry, giving you a tremendous opportunity for both scope & impact. Responsibilities - Inspire, lead, and grow a team of data scientists to achieve our longer term vision - Drive data science projects end-to-end in partnership with Product, Engineering, and other partners to inform product strategy and investment decisions - Analyze large datasets to identify trends, patterns, and insights that can help understand marketplace dynamics and help cross-functional teams (e.g., product, engineering, marketing) to define and execute data-driven optimization strategies - Actively influence the design of the strategy and shaping of the roadmap. Generate and use team insights to set and prioritize longer term goals - Create and implement A/B testing, experimentation, and other cutting-edge statistical/mathematical frameworks to analyze Ads (marketplace) performance - Continually develop & execute on a Data Science roadmap and vision for your team - Stay abreast of industry best practices and emerging technologies in the field of advertising and data science - Foster a culture of innovation, collaboration, and technical excellence - Be an integral part of the Data Science Org, leveraging and contributing to the vibrant knowledge base, shared across a community of world-class data experts Required Qualifications - PhD or Master's degree in Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields (If M.S. degree, a minimum of 8+ years of industry data science experience required; If PhD degree, a minimum of 6+ years of industry data science experience required) - 4+ years of management experience. Experience managing managers is a bonus. - Strong skills in programming (Python or R) and SQL - Experience in leveraging AI-assisted development tools (e.g., Cursor, Claude, or similar LLMs) to improve personal and team productivity, code quality, and technical problem-solving. - Deep understanding of Ads Marketplace - Extensive experience of online experimentation and causal inference - Ability to communicate & discuss low-level technical topics as well as high-level strategies. - Comfortable in innovative and fast-paced environments, and an innate ability to bias toward action - Results-oriented with a strong customer and business focus - Track-record driving product roadmap and execution with strong cross-org collaborations - Ability to provide structure and tackle ambiguous and undefined problems Benefits: - Comprehensive Healthcare Benefits and Income Replacement Programs - 401k with Employer Match - Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support - Family Planning Support - Gender-Affirming Care - Mental Health & Coaching Benefits - Flexible Vacation & Paid Volunteer Time Off - Generous Paid Parental Leave #LI-Remote Pay Transparency: This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit https://www.redditinc.com/careers/. To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below. The base salary range for this position is: $232,500—$325,500 USD In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews. During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors. Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.

• 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