Rich’s, also known as Rich Products Corporation, is a family-owned food company dedicated to inspiring possibilities. From cakes and icings to pizza, appetizers and specialty toppings, our products are used in homes, restaurants and bakeries around the world. Beyond great food, our customers also gain insights to help them stay competitive, no matter their size. Our portfolio includes creative solutions geared at helping food industry professionals compete in foodservice, retail, in-store bakery, deli, and prepared foods, among others. Working in 100 locations globally, with annual sales exceeding $4 billion, Rich’s is a global leader with a focus on everything that family makes possible. Rich’s®—Infinite Possibilities. One Family. Purpose Statement Rich’s, also known as Rich Products Corporation, is a family-owned food company dedicated to inspiring possibilities. From cakes and icings to pizza, appetizers and specialty toppings, our products are used in homes, restaurants and bakeries around the world. Beyond great food, our customers also gain insights to help them stay competitive, no matter their size. Our portfolio includes creative solutions geared at helping food industry professionals compete in foodservice, retail, in-store bakery, deli, and prepared foods, among others. Working in 100 locations globally, with annual sales exceeding $4 billion, Rich’s is a global leader with a focus on everything that family makes possible. Rich’s®—Infinite Possibilities. One Family. The Data Science/AI Intern will collaborate with the Data, AI, and Analytics team to support real-world projects involving data exploration, modeling, and visualization. This role is designed to provide hands-on experience in applying data science techniques to solve business challenges and generate actionable insights. We are happy to consider remote candidates for this role. Key Accountabilities and Outcomes • Data Collection & Cleaning: Gather, preprocess, and validate datasets from internal and external sources. • Exploratory Data Analysis (EDA): Identify trends, patterns, and anomalies using statistical and visual techniques. • Model Development: Build and evaluate predictive models using machine learning algorithms. • Visualization & Reporting: Create dashboards and visual reports to communicate findings to stakeholders. • Documentation: Maintain clear records of methodologies, code, and project outcomes. • Collaboration: Work closely with cross-functional teams to align data solutions with business needs. Knowledge, Skills, and Experience • Must be enrolled in a Data Science/AI/Machine Learning (or closely related subject) degree program and expect to be for the duration of the internship. • Prior coursework or projects in machine learning, statistical modeling, or data visualization. • Exposure to real-world datasets and business applications. • Proficiency in Python, and SQL for data manipulation and analysis. • Understanding of statistical methods and hypothesis testing for data interpretation. • Exposure to cloud environments such as Azure or Databricks preferred. #LI-NT1 #INTERN123 COMPENSATION In accordance with state law, the rate or range provided is Rich Products Corporation, its subsidiaries and affiliates ("Rich's"), reasonable estimate of the base compensation for this role. The actual amount may be higher or lower, based on non-discriminatory factors such as experience, knowledge, skills, abilities, shift differential, and location. Annual Range/Hourly Rate $17.00 - $23.00 Rich Products Corporation, its subsidiaries and affiliates (“Rich’s”), are committed to a policy of Equal Employment Opportunity, standing up for fairness and maintaining a culture of belonging, to provide an exceptional experience for all. We will not discriminate against an applicant or employee on the basis of race, color, religion, sex, national origin, disability, military or veteran status, or any other Federal or State legally protected classes. The information collected by this application is solely to determine suitability for employment, verify identity, and maintain employment statistics on applicants. Applicants with disabilities may be entitled to reasonable accommodation under the Americans with Disabilities Act and certain state or local laws. A reasonable accommodation is a change in the way things are normally done which will ensure an equal employment opportunity without imposing undue hardship on Rich’s. Please contact Rich’s Associate Experience Network at hrhelp@rich.com if you need assistance completing this application or to otherwise participate in the application process.

At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts. Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet. Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all. About the team and the role: At eBay, we connect millions of buyers and sellers around the world, creating economic opportunity for individuals, entrepreneurs, and businesses of all sizes. Our Seller Experience team is focused on making it easier and faster for anyone to sell on eBay by demonstrating AI, automation, and intuitive product design. We are seeking a Data Scientist to help shape the future of AI-powered selling experiences. In this role, you will partner closely with Product and Engineering teams to develop analytics, experimentation strategies, and data-driven insights that simplify listing flow, improve listing quality, and accelerate seller growth. You will work on high-impact initiatives such as AI-assisted listing flows, personalized seller guidance, LLM-powered insights, and scalable experimentation frameworks that directly influence product roadmap and business outcomes. This role is ideal for a strong senior data scientist who can independently own analytics workstreams, apply structured thinking to ambiguous problems, and translate data into actionable recommendations that improve both user experience and business performance. What you will accomplish: - Design, implement, and analyze A/B tests to evaluate product features and AI-powered experiences - Define success metrics, measurement frameworks, and experimentation strategies to support product development and launches - Analyze user behavior, product funnels, and engagement patterns to find opportunities to improve seller activation, efficiency, and success - Partner closely with Product and Engineering teams to inform roadmap prioritization, feature design, and iteration decisions - Build scalable data pipelines, dashboards, and monitoring tools to track product performance and experimentation results - Find opportunities to harness AI and advanced analytics to improve seller experience and product effectiveness - Translate complex analyses into clear, actionable insights and recommendations for technical and non-technical partners - Improve analytics workflows and tooling to increase insights velocity, scalability, and impact - Ensure data quality, tracking integrity, and measurement reliability to support accurate experimentation and decision-making What you will bring: - Master’s degree in Data Science, Statistics, Economics, Computer Science, or a related quantitative field - 4+ years of professional experience in product analytics, data science, or a related analytical role - Strong SQL skills and experience working with large-scale, complex datasets - Hands-on experience designing, executing, and analyzing A/B tests - Solid foundation in statistics, experimentation, modeling and causal inference - Strong analytical thinking, problem-solving, and structured reasoning skills - Experience partnering cross-functionally with Product and Engineering teams - Ability to independently own analyses and translate data into actionable product insights - Strong communication skills with the ability to influence both technical and non-technical partners Preferred Qualifications: - Experience working on marketplace, e-commerce platforms or large-scale technology products - Experience with AI-powered product features or LLM/GenAI - Experience building scalable analytics tools, data models, or experimentation frameworks Why Join this Team: You will play a key role in crafting the future of AI-powered selling at eBay. Your work will directly influence product strategy, accelerate innovation, and improve the experience for millions of sellers worldwide. You will operate at the intersection of analytics, product, and AI—solving high-impact problems and helping drive marketplace growth through data-driven decision-making. Additional Details The base pay range for this position is expected in the range below: $103,200 - $178,400 Base pay offered may vary depending on multiple individualized factors, including location, skills, and experience. The total compensation package for this position may also include other elements, including a target bonus and restricted stock units (as applicable) in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as PTO and parental leave). Details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employees will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors. eBay is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status. If you have a need that requires accommodation, please contact us at talent@ebay.com. We will make every effort to respond to your request for accommodation as soon as possible. View our accessibility statement to learn more about eBay's commitment to ensuring digital accessibility for people with disabilities. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. We use cookies to enhance your experience and may use AI tools for administrative tasks in the hiring process. To learn how we handle your personal data and use AI responsibly, please visit our Talent Privacy Notice, Privacy Center, and AI Hiring Guidelines.

• Guide and optimize spend so it scales efficiently under contribution margin guardrails • Define CAC ceilings tied to 12- and 24-month contribution margin • Model diminishing returns and marginal efficiency curves to inform budget allocation • Translate attribution constraints and measurement uncertainty into practical, decision-ready frameworks • Interpret insights from MMM, incrementality tests, lift studies, or MTA frameworks and translate them into practical budget and investment decisions • Identify which channels, audiences, creatives, and offers drive the highest-quality cohorts • Support structured validation of new channels before meaningful scale • Deliver clear monthly recommendations on where to scale, hold, or cut • Build and maintain 12- and 24-month contribution margin tracking by acquisition cohort • Develop survival curve diagnostics and retention performance visibility across key milestones • Operationalize retention-adjusted CAC and payback thinking into acquisition decisions • Identify acquisition sources that degrade churn, payback, LTV, or margin • Evaluate pricing, discounts, and offers against downstream margin impact • Create cohort-based forecasting views that improve decision quality without turning this role into FP&A • Own tracking health across ad platforms, GA4, server-side events, ecommerce, and subscription systems • Standardize UTMs, taxonomy, and core metric definitions so performance reporting is trusted • Partner with Finance to align revenue, refunds, COGS, and contribution margin inputs • Build automated dashboards and reduce manual reporting • Create a clear source of truth for acquisition efficiency and long-term cohort performance • Analyze tests and performance shifts across pricing, trial structure, billing cadence, onboarding, churn interventions, win-back, and upsell • Provide decision criteria rooted in long-term contribution margin, not isolated metric lifts • Deliver clear narratives on what changed, why it changed, and what to do next

• Develop and deploy scalable machine learning and AI solutions in production environments, ensuring performance and sustainability • Build and refine models for customer segmentation, risk prediction, clinical decision support, and other healthcare-specific use cases • Ensure rigorous use of statistical methods, reproducibility, and documentation across all projects • Design and implement statistical tests, A/B experiments, and performance monitoring strategies • Evaluate ML/AI models and products for fairness in output, targeting and actions • Partner with stakeholders to define problem statements, identify data sources, and design effective solutions • Build and maintain robust data pipelines, modeling workflows, and monitoring tools in collaboration with engineering and data platform teams • Partner with senior and executive leadership to define and advance the enterprise AI roadmap, identifying high-impact opportunities to embed ML and AI services into core business workflows • Lead multiple high-impact data science projects across areas including Clinical, STARs, Risk Adjustment, Claims, Pharmacy, Marketing and Member Experiences • Manage and mentor a team of data scientists; provide technical guidance via review of code, models, and analytical approaches; foster professional growth; and drive a culture of experimentation and continuous learning