ABOUT THRIVE MARKET Thrive Market was founded in 2014 with a mission to make healthy and sustainable living easy and affordable for everyone. As an online, membership-based market, we deliver the highest quality healthy, and sustainable products at member-only prices, while matching every paid membership with a free one for someone in need. Every day, we leverage innovative technology and member-first thinking to help our over 1,700,000+ members find better products, support better brands, and build a better world in the process. We are also a Certified B Corporation, a Public Benefit Corporation, and a Climate Neutral Certified company. Join us as we bring healthy and sustainable living to millions of Americans in the years to come. THE ROLE At Thrive Market, our ML (Data Science) team drives meaningful impact for both our members and the business by transforming data into insights, models, and systems that shape every part of the e-commerce grocery journey. From powering search, recommenders and personalization to optimizing lifecycle engagement, our data scientists ensure decision-making and product experiences are grounded in rigorous analysis and scalable intelligence. We’re looking for a Senior Data Scientist to play a critical role within our ML team. In this role, you’ll own high-impact analytical and modeling initiatives end-to-end, partnering closely with Product, Engineering, and Analytics to influence strategy, improve customer experience, and drive measurable business outcomes. You will be expected to operate with significant autonomy, demonstrate strong judgment in problem framing and solution design, and raise the overall bar for data science excellence across the organization. RESPONSIBILITIES: - Own and deliver high-impact data science initiatives, from problem definition and data exploration to modeling, validation, and productionization, driving measurable improvements in customer experience and business metrics. - Partner closely with Product, Engineering, and Analytics to shape roadmaps, define success metrics, and translate ambiguous business problems into well-scoped analytical or modeling solutions. - Partner with Engineering and Devops to deploy, operate, and scale ML workloads using cloud-native infrastructure and MLOps tooling (e.g., AWS SageMaker, Lambda, S3, ECR, Docker, Kubernetes). - Design, build, and iterate on statistical models, machine learning systems, and decision frameworks (e.g., personalization, ranking, forecasting, experimentation analysis). - Lead rigorous experimentation and measurement practices, including A/B test design, hypothesis formulation, metric selection, causal inference, and interpretation of results. - Communicate insights, trade-offs, and recommendations clearly to both technical and non-technical stakeholders, influencing decisions at the pod and org level. - Ensure high standards of quality and reliability in data science outputs through code reviews, model validation, documentation, and monitoring. - Proactively identify opportunities and risks in data, modeling, or experimentation approaches, and drive improvements that enhance scalability, accuracy, and long-term impact. - Mentor and support other data scientists through technical guidance, feedback, and best-practice sharing, without direct people management responsibility. QUALIFICATIONS: - 5+ years of experience in data science, applied machine learning, or a related quantitative role, with demonstrated ownership of end-to-end projects. - Strong grounding in ML, statistics, experimentation and data analysis, including hypothesis testing, causal reasoning, and metric design. - Experience building and deploying production-grade models or analytical systems in collaboration with engineering teams, including hands-on experience with cloud-based ML infrastructure (e.g., AWS SageMaker, Lambda, S3, ECR) and containerized workflows (Docker, Kubernetes). - Proven experience designing, analyzing, and interpreting A/B tests in production environments, aligned to business or product goals, including defining success metrics and guarding against common statistical pitfalls. - Ability to work effectively with cross-functional partners (Product, Engineering, Analytics, Design, Data Engineering), translating between business context and technical solutions. - Strong problem-framing and prioritization skills, particularly in ambiguous or under-specified problem spaces. - Proficiency in SQL and Python, with experience using modern data and ML tooling. - Ownership mindset: proactively identifying problems worth solving, taking accountability for outcomes, and driving initiatives forward independently. PREFERRED: - Hands-on experience with search, personalization, recommendations, ranking, or lifecycle modeling. - Experience with MLOps best practices, including model versioning, CI/CD for ML, monitoring, and operating models in containerized and orchestrated environments (Docker, Kubernetes). - Experience in e-commerce, marketplace, or subscription-based businesses. - Familiarity with working in environments with moderate technical debt or evolving data foundations. - Experience defining and owning metrics, experimentation frameworks, or model performance monitoring in production. - Demonstrated ability to influence beyond immediate project scope, shaping best practices, standards, or strategy across teams. BELONG TO A BETTER COMPANY: - Comprehensive health benefits (medical, dental, vision, life and disability) - Competitive salary (DOE) + equity - 401k Employer Match - 9 Days of Observed Holidays - Flexible Paid Time Off - Subsidized ClassPass Membership with access to fitness classes and wellness and beauty experiences - Ability to work in our beautiful office in Playa Vista - Free Thrive Market membership with exclusive employee discount - Coverage for Life Coaching & Therapy Sessions on our holistic mental health and well-being platform We're a community of more than 1 Million + members who are united by a singular belief: It should be easy to find better products, support better brands, make better choices, and build a better world in the process. At Thrive Market, we believe in building a diverse, inclusive, and authentic culture. If you are excited about this role along with our mission and values, we encourage you to apply. Thrive Market is an EEO/Veterans/Disabled/LGBTQ employer At Thrive Market, our goal is to be a diverse and inclusive workplace that is representative, at all job levels, of the members we serve and the communities we operate in. We’re proud to be an inclusive company and an Equal Opportunity Employer and we prohibit discrimination and harassment of any kind. We believe that diversity and inclusion among our teammates is critical to our success as a company, and we seek to recruit, develop and retain the most talented people from a diverse candidate pool. If you’re thinking about joining our team, we expect that you would agree! Employment with Thrive Market requires that employees be based in the United States. This is a condition of employment and must be maintained throughout the duration of employment. If you need assistance or accommodation due to a disability, please email us at eeo@thrivemarket.com and we’ll be happy to assist you. Ensure your Thrive Market job offer is legitimate and don't fall victim to fraud. Thrive Market never seeks payment from job applicants. Thrive Market recruiters will only reach out to applicants from an @thrivemarket.com email address. For added security, where possible, apply through our company website at www.thrivemarket.com. © Thrive Market 2026 All rights reserved. JOB INFORMATION - Compensation Description - The base salary range for this position is $175,000 - $190,000/Per Year. - Compensation may vary outside of this range depending on several factors, including a candidate’s qualifications, skills, competencies and experience, and geographic location. - Total Compensation includes Base Salary, Stock Options, Health & Wellness Benefits, Flexible PTO, and more! - This position requires traveling to our HQ office in Los Angeles, California, twice a year for all-company summits; once in the summer and once in the winter.

Role Description We are looking for a Risk & Payments Intelligence Analyst to join our Risk & Fraud team. In this role, you will analyze data related to ACH transactions, ML risk scores, risk rules, decisioning systems, and vendor data to understand performance, surface emerging trends, and inform ongoing optimization of payment program decisions. This role focuses on portfolio and system level analysis rather than case-by-case transaction review or manual queues, and requires strong analytical judgment in ambiguous, data-constrained environments, including the evaluation of new data, analytical methods, and AI-assisted approaches as our risk capabilities evolve. Key Responsibilities - Analyze end-to-end ACH payment decisioning performance, including ML risk scores and risk rules, across approvals and losses. - Detect and analyze emerging trends in customer behavior, payment outcomes, and risk signals. - Evaluate how changes in strategies, data, or rules impact downstream decisioning and outcomes over time. - Independently define analytical questions, assemble datasets from multiple sources, and iterate toward insights without predefined reporting templates. - Use Python to perform exploratory data analysis, feature evaluation, cohort analysis, and experimentation across large ACH and risk datasets. - Develop repeatable analytical workflows and lightweight tooling in Python to accelerate insight generation and reduce manual analysis overhead. - Perform ad hoc analyses to evaluate the value and usefulness of new or existing data signals for risk decisioning. - Design analyses and reporting that support ongoing risk reviews, strategy discussions, and portfolio-level monitoring. - Explore and apply established and emerging analysis techniques to accelerate insight generation, trend detection, and decision support within regulated risk and payment datasets. - Partner with Risk, Product, and Relationship Management teams to inform strategy refinement and prioritization. - Communicate trends, findings, and recommendations clearly to internal stakeholders and, when applicable, external clients. - Work with large, imperfect, and regulated datasets to form actionable conclusions despite data gaps, latency, or attribution challenges. Qualifications - 3+ years of experience in payments risk, fraud analytics, or decisioning performance analysis within fintech, payments, or e-commerce. - Experience working with ACH or bank transfer payment data strongly preferred. - Strong SQL skills and experience working with large transactional datasets. - Strong Python skills for data analysis (e.g., pandas, notebooks), experimentation, and analytical automation. - Experience managing and analyzing data related to risk-based decision systems, or similar decisioning frameworks. - Ability to translate complex analytical findings into clear, actionable recommendations for technical and non-technical audiences. - Comfort operating in ambiguous environments with incomplete, delayed, or imperfect data. - Experience using AI-assisted tools or models for data analysis, pattern discovery, or insight generation is a plus. Working Language English (written and spoken) is the language used most of the time, as work colleagues, clients, and strategic suppliers are geographically dispersed. Recruitment Process Our recruitment process may use automated tools, including AI, to support application management and candidate shortlisting.

• Conduct various analyses to understand the data and generate business insights; • Develop statistical models using a range of techniques; • Continuously refine and improve developed statistical models; • Monitor the performance of production statistical models; • Serve as a technical reference for other professionals in the area; • Support the technical development of new business needs; • Lead research projects aimed at opening new paths in data analysis; • Create high-impact Data Science projects; • Present model results to business areas to highlight the importance of model deployment, communicate the insights obtained, and translate model outputs into business terms.

• Organize and evolve the Pix squads' workflow • Support the structuring of initiatives and ensure their execution with quality and predictability • Work closely with Engineering, Design, and Data teams • Organize and maintain a structured, up-to-date backlog, ensuring clarity and prioritization of initiatives • Assist in writing user stories, documentation, and defining flows • Ensure initiatives are ready for development • Monitor progress of tasks and deliverables • Identify and flag blockers, dependencies, and gaps • Support alignment between Product, Engineering, and stakeholders • Ensure visibility of the workflow • Run the squad's operational rituals • Drive continuous improvement of the development flow