Role Description As a Senior Data Scientist, reporting to the Head of Data Science in our Data & Analytics team, your purpose will be to build and own machine learning powered features that directly improve our customer app and marketplace experience. - Work on customer-facing problems such as: - Search and ranking - Recommendations - Segmentation - Lifecycle modelling including activation, churn, and reactivation - Lead scoring - Personalization - Operate end to end, from shaping ambiguous product ideas into clearly defined problems, through modelling and experimentation, to deploying and monitoring production systems. - Take real ownership, which may include: - Contributing to data pipelines - Partnering closely with engineers on real-time systems - Ensuring models are robust, scalable, and measurable against business KPIs such as conversion, retention, and revenue. - Collaborate cross-functionally with Product, Engineering, Marketing, and Pricing, acting as both a technical expert and a structured problem-solver. Qualifications - Proven experience delivering machine learning solutions end to end in production, ideally in a marketplace or customer-facing product environment. - Strong experience with behavioural and customer data, including segmentation, lifecycle modelling, scoring, search, or recommendation systems. - Strong Python and SQL skills, with the ability to work across modelling and data preparation. - Experience working with cloud platforms, GCP preferred and AWS also welcome, and understanding how data pipelines are built and maintained. - Demonstrated ability to define problems clearly, engage stakeholders, and communicate impact in commercial environments. - Conversational-level English language skills. Requirements - Experience applying NLP and LLMs to real product use cases. Generative AI is a plus but not the whole role. - Experience working with real-time or near real-time systems. - Exposure to pricing or marketing optimisation problems. Benefits - This is a fully remote position. We take pride in being a globally distributed team. - A generous holiday allowance of 26 days plus public holidays. - Access to a global learning and development program, wellness benefits, and discounts across partner platforms.

Title: Senior Scientist, Claims Excellence Location: North America, United States, New Jersey, Summit Job Description: Kenvue is currently recruiting for a: Senior Scientist, Claims Excellence What we do At Kenvue, we realize the extraordinary power of everyday care. Built on over a century of heritage and rooted in science, we’re the house of iconic brands - including NEUTROGENA®, AVEENO®, TYLENOL®, LISTERINE®, JOHNSON’S® and BAND-AID® that you already know and love. Science is our passion; care is our talent. Who We Are Our global team is ~ 22,000 brilliant people with a workplace culture where every voice matters, and every contribution is appreciated.We are passionate about insights, innovation and committed to delivering the best products to our customers. With expertise and empathy, being a Kenvuer means having the power to impact millions of people every day. We put people first, care fiercely, earn trust with science and solve with courage – and have brilliant opportunities waiting for you! Join us in shaping our future–and yours. Role reports to: Claims Excellence Lead Self Care Location: North America, United States, New Jersey, Summit Work Location: Hybrid What you will do This position serves as a key member of the Translational Science Claims Excellence team, driving the development and execution of claims strategies and roadmaps for new product and innovation projects. The individual will contribute scientific expertise to strengthen claims, support study execution, and ensure timely project delivery. This role partners cross-functionally with R&D and global stakeholders to translate complex scientific insights into clear, compelling claims and messaging for both consumers and healthcare professionals. Key Responsibilities - Serve as a member of the Translational Science Claims Excellence team dedicated to the development of the claims strategy and implementation of claim roadmaps and creative claims support strategies for new product or claim innovation projects, working cross-functionally across R&D subject matter experts. - Play a claims subject matter expert role in understanding the relevant science to provide contributions, translations and/or make recommendations to strengthen claims and or science storytelling to cross-functional and global project teams within R&D. - Communicate and translate scientific and technical knowledge for consumer-facing and healthcare professional message development. - Participate on global, cross functional teams for evaluation of new product ideas and project implementation, providing active scientific contributions and ensuring timeline adherence and project completion of claims approvals and corresponding studies. - Champion the new Kenvue Human Centered Innovation mindset, claims process and claims system. What We Are Looking For Required Qualifications - Strong collaboration, influence, and decision-making skills, along with the ability to manage routine processes and consider measured risks, are critical components of the role. ​ - Bachelor's degree with at least 3 years or Master’s/PharmD/PhD degree with 2+ years of Consumer/OTC/pharmaceutical (or equivalent) industry and/or relevant work experience. - Education to include scientific fields such as health sciences, biology, chemistry, engineering, sensory, or pharmaceutical science is preferred. - Experience in developing compelling claims & communication strategies and translating scientific evidence into robust claims substantiation. - Ability and flexibility to work in a global environment. - The ability to work in a matrix environment with cross-functional teams and have excellent verbal and written communication skills is essential - Must be able to work independently, think analytically, manage multiple complex tasks, while also being highly detail oriented and organized. What’s in it for you Annual base salary for new hires in this position ranges: $105,400.00 - $148,800.00 This takes into account a number of factors including work location, the candidate’s skills, experience, education level & other job-related factors. - Competitive Benefit Package* - Paid Company Holidays, Paid Vacation, Volunteer Time & More! - Learning & Development Opportunities - Kenvuer Impact Networks - This list could vary based on location/region *Note: Total Rewards at Kenvue include salary, bonus (if applicable) and benefits. Your Talent Access Partner will be able to share more about our total rewards offerings and the specific salary range for the relevant location(s) during the recruitment & hiring process. Kenvue is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment based on merit without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability. If you are an individual with a disability, please check our Disability Assistance page for information on how to request an accommodation.

Title: Senior Staff Data Scientist Location: New York, NY Job Description: About Grubhub At Grubhub, we believe food is more than just a meal: It’s a source of discovery, connection, and pure enjoyment. There’s a time and place for every type of dish, from hidden neighborhood gems to tried-and-true favorites, and we exist to connect people with the food they love in all the ways they like to dig in. We’ve been at it since 2004, but now, as part of Wonder, Grubhub is operating with a renewed sense of momentum and the high-velocity energy of a powerhouse startup. As a leading U.S. ordering and delivery marketplace, we feature over 415,000 merchants in more than 4,000 cities, creating the ultimate food experience by elevating online ordering through innovative restaurant technology, easy-to-use platforms, and an improved delivery experience. We are constantly finding new ways to innovate—from integrated grocery delivery with groceries powered by Instacart to exclusive loyalty programs. Join our team, based out of New York City, Chicago and Denver, and help us give our diners the exceptional value they deserve. About the Opportunity At Wonder Data Science, our mission is to build data science and machine learning systems that improve how our marketplace operates, how customers experience the platform, and how the business makes high-quality decisions. As a Senior Staff Data Scientist, you will go beyond individual problem solving — you will help shape the strategic direction of applied data science, mentor senior and junior scientists, and collaborate closely with engineering, product, operations, and business leaders to move our ML and analytics capabilities toward scalable, production-grade systems. You will identify high-leverage opportunities across the business, including marketplace efficiency, customer experience, ETA accuracy, fulfillment reliability, pricing strategy, supply planning, demand forecasting, and operational performance. You will design statistically rigorous frameworks to understand causal impact, separate signal from noise, and guide business strategy through experimentation, measurement, and principled inference. You will help define how we structure trade-offs like customer experience vs. operational efficiency, speed vs. cost, prediction accuracy vs. business impact, short-term metric movement vs. long-term marketplace health, and automation vs. human judgment. You’ll prototype, experiment, influence architecture, and ensure we operationalize models and insights that actually move business metrics — not just analyses that look good offline. The Impact You Will Make - Serve as a technical thought leader in Data Science — defining principles, frameworks, and best practices for how Wonder uses data, experimentation, and machine learning to improve customer, marketplace, and business outcomes. - Mentor and coach a growing team of Data Scientists and contribute to career development and technical excellence across the group. - Lead the exploration of interconnected marketplace systems, recognizing feedback loops between customer behavior, fulfillment reliability, ETA accuracy, pricing, supply planning, product experience, and business performance. - Develop causal inference and experimentation frameworks that help Wonder understand which product, operational, and marketplace changes truly drive business impact. - Partner with engineering to drive architecture decisions for shared data layers, feature pipelines, modeling APIs, experimentation infrastructure, and production ML services. - Define and implement robust experimentation strategies for changes that move business metrics in high-noise environments. - Champion business-impact-driven data science, integrating causal inference, experimentation, risk-aware modeling, and scalable production ML systems that learn and adapt. What You Bring to the Table - 8+ years of industry experience with MS or 6+ years with PhD in Statistics, Economics, Applied Mathematics, Computer Science, Data Science, Machine Learning, or a related quantitative field. - Proven experience applying data science and machine learning to complex business problems, such as marketplace optimization, customer experience, forecasting, personalization, pricing, supply/demand balancing, operational policy changes, or product experimentation. - Deep expertise in causal inference, experimentation, and statistical modeling, including methods such as A/B testing, difference-in-differences, regression discontinuity, instrumental variables, synthetic controls, uplift modeling, or causal impact analysis. - Strong intuition for business and product trade-offs — customer experience vs. efficiency, ETA confidence vs. conversion risk, fulfillment reliability vs. cost, marketplace growth vs. quality, and short-term optimization vs. long-term health. - Proficiency in Python, data analysis, visualization, and writing scalable, production-ready code using object-oriented design. - Demonstrated ability to take data science, ML, or causal inference systems into production, partnering with engineering on architecture, deployment, and monitoring best practices. - Fluency in SQL or similar tools for directly interrogating production-scale datasets. - Experience mentoring and providing technical direction to other scientists, analysts, or engineers. Got These? Even Better - Experience leading end-to-end design of data science, machine learning, measurement, or experimentation frameworks within marketplace, consumer product, fulfillment, logistics, pricing, forecasting, or operations systems. - Experience designing causal measurement strategies for complex systems where product, marketplace, and operational decisions interact across multiple layers. - Background in causal inference, econometrics, Bayesian modeling, experimental design, or observational measurement in high-noise environments. - Experience with applied experimentation frameworks, including A/B testing, power analysis, heterogeneous treatment effects, guardrail metrics, interference effects, and long-term impact measurement. - Experience building or influencing production ML systems that combine predictive modeling, causal measurement, experimentation, and business rules - Influence across disciplines — able to align product, engineering, operations, business, and data science around a cohesive ML, experimentation, and measurement strategy. - Experience defining strategy and technical roadmaps for data science, machine learning, experimentation, or causal inference platforms. Our hybrid model requires 3 days a week in the office. That said, many team members choose to come in more often to take advantage of in-person collaboration and connection. You're welcome—and encouraged—to be in the office up to 5 days a week if it works for you. #LI-Hybrid New York: $240,000 - $249,500 per year. Illinois: $216,000 - $224,500 per year. Wonder uses geographic-specific salary structures, which means the salary offered may vary depending on where the job is located. The final salary offer will take into account various factors, such as the candidate's skills, education, training, credentials, and experience. Benefits We offer a competitive salary package including equity and 401K. Additionally, we provide multiple medical, dental, and vision plans to meet all of our employees' needs as well as many benefits and perks that are not listed.  A Final Note At Wonder, we build the best teams by hiring with an objective lens — evaluating people for their potential while championing diversity, equity, and inclusion. We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, military service eligibility, veteran status, marital status, disability, or any other protected class. As part of our commitment to fair and compliant hiring practices, Wonder participates in the federal government's E-Verify program to confirm employment eligibility. If you need an accommodation during the interview process, please let your recruiter know. We look forward to hearing from you! We'll contact you via email or text to schedule interviews and share information about your candidacy.

Title: Senior Staff Data Scientist Location: New York, NY Job Description: Full time job requisition id JR101139 About Grubhub At Grubhub, we believe food is more than just a meal: It’s a source of discovery, connection, and pure enjoyment. There’s a time and place for every type of dish, from hidden neighborhood gems to tried-and-true favorites, and we exist to connect people with the food they love in all the ways they like to dig in. We’ve been at it since 2004, but now, as part of Wonder, Grubhub is operating with a renewed sense of momentum and the high-velocity energy of a powerhouse startup. As a leading U.S. ordering and delivery marketplace, we feature over 415,000 merchants in more than 4,000 cities, creating the ultimate food experience by elevating online ordering through innovative restaurant technology, easy-to-use platforms, and an improved delivery experience. We are constantly finding new ways to innovate—from integrated grocery delivery with groceries powered by Instacart to exclusive loyalty programs. Join our team, based out of New York City, Chicago and Denver, and help us give our diners the exceptional value they deserve. About the Opportunity At Wonder Data Science, our mission is to build data science and machine learning systems that improve how our marketplace operates, how customers experience the platform, and how the business makes high-quality decisions. As a Senior Staff Data Scientist, you will go beyond individual problem solving — you will help shape the strategic direction of applied data science, mentor senior and junior scientists, and collaborate closely with engineering, product, operations, and business leaders to move our ML and analytics capabilities toward scalable, production-grade systems. You will identify high-leverage opportunities across the business, including marketplace efficiency, customer experience, ETA accuracy, fulfillment reliability, pricing strategy, supply planning, demand forecasting, and operational performance. You will design statistically rigorous frameworks to understand causal impact, separate signal from noise, and guide business strategy through experimentation, measurement, and principled inference. You will help define how we structure trade-offs like customer experience vs. operational efficiency, speed vs. cost, prediction accuracy vs. business impact, short-term metric movement vs. long-term marketplace health, and automation vs. human judgment. You’ll prototype, experiment, influence architecture, and ensure we operationalize models and insights that actually move business metrics — not just analyses that look good offline. The Impact You Will Make - Serve as a technical thought leader in Data Science — defining principles, frameworks, and best practices for how Wonder uses data, experimentation, and machine learning to improve customer, marketplace, and business outcomes. - Mentor and coach a growing team of Data Scientists and contribute to career development and technical excellence across the group. - Lead the exploration of interconnected marketplace systems, recognizing feedback loops between customer behavior, fulfillment reliability, ETA accuracy, pricing, supply planning, product experience, and business performance. - Develop causal inference and experimentation frameworks that help Wonder understand which product, operational, and marketplace changes truly drive business impact. - Partner with engineering to drive architecture decisions for shared data layers, feature pipelines, modeling APIs, experimentation infrastructure, and production ML services. - Define and implement robust experimentation strategies for changes that move business metrics in high-noise environments. - Champion business-impact-driven data science, integrating causal inference, experimentation, risk-aware modeling, and scalable production ML systems that learn and adapt. What You Bring to the Table - 8+ years of industry experience with MS or 6+ years with PhD in Statistics, Economics, Applied Mathematics, Computer Science, Data Science, Machine Learning, or a related quantitative field. - Proven experience applying data science and machine learning to complex business problems, such as marketplace optimization, customer experience, forecasting, personalization, pricing, supply/demand balancing, operational policy changes, or product experimentation. - Deep expertise in causal inference, experimentation, and statistical modeling, including methods such as A/B testing, difference-in-differences, regression discontinuity, instrumental variables, synthetic controls, uplift modeling, or causal impact analysis. - Strong intuition for business and product trade-offs — customer experience vs. efficiency, ETA confidence vs. conversion risk, fulfillment reliability vs. cost, marketplace growth vs. quality, and short-term optimization vs. long-term health. - Proficiency in Python, data analysis, visualization, and writing scalable, production-ready code using object-oriented design. - Demonstrated ability to take data science, ML, or causal inference systems into production, partnering with engineering on architecture, deployment, and monitoring best practices. - Fluency in SQL or similar tools for directly interrogating production-scale datasets. - Experience mentoring and providing technical direction to other scientists, analysts, or engineers. Got These? Even Better - Experience leading end-to-end design of data science, machine learning, measurement, or experimentation frameworks within marketplace, consumer product, fulfillment, logistics, pricing, forecasting, or operations systems. - Experience designing causal measurement strategies for complex systems where product, marketplace, and operational decisions interact across multiple layers. - Background in causal inference, econometrics, Bayesian modeling, experimental design, or observational measurement in high-noise environments. - Experience with applied experimentation frameworks, including A/B testing, power analysis, heterogeneous treatment effects, guardrail metrics, interference effects, and long-term impact measurement. - Experience building or influencing production ML systems that combine predictive modeling, causal measurement, experimentation, and business rules - Influence across disciplines — able to align product, engineering, operations, business, and data science around a cohesive ML, experimentation, and measurement strategy. - Experience defining strategy and technical roadmaps for data science, machine learning, experimentation, or causal inference platforms. Our hybrid model requires 3 days a week in the office. That said, many team members choose to come in more often to take advantage of in-person collaboration and connection. You're welcome—and encouraged—to be in the office up to 5 days a week if it works for you. #LI-Hybrid New York: $240,000 - $249,500 per year. Illinois: $216,000 - $224,500 per year. Wonder uses geographic-specific salary structures, which means the salary offered may vary depending on where the job is located. The final salary offer will take into account various factors, such as the candidate's skills, education, training, credentials, and experience. Benefits We offer a competitive salary package including equity and 401K. Additionally, we provide multiple medical, dental, and vision plans to meet all of our employees' needs as well as many benefits and perks that are not listed.  A Final Note At Wonder, we build the best teams by hiring with an objective lens — evaluating people for their potential while championing diversity, equity, and inclusion. We do not discriminate based on race, color, religion, gender identity or expression, sexual orientation, national origin, age, military service eligibility, veteran status, marital status, disability, or any other protected class. As part of our commitment to fair and compliant hiring practices, Wonder participates in the federal government's E-Verify program to confirm employment eligibility. If you need an accommodation during the interview process, please let your recruiter know. We look forward to hearing from you! We'll contact you via email or text to schedule interviews and share information about your candidacy.