Senior Data Analyst (Product & Engineering)
6 days ago
New York
Job DescriptionWant to be a part of a team revolutionizing and leading an entire industry with no real competition? The laundry industry is a $40+ billion dollar market, and the Cents platform is making it easier for laundromats, dry cleaners, and all garment care businesses to grow, manage, and understand their business. Backed by top-tier investors like Bessemer, Camber Creek, and Tiger Global, Cents is one of the fastest-growing vertical SaaS companies in the USA, and we’re just getting started. Already profitable and growing incredibly quickly each year, we have entered the absolute best stage of being a startup. About CentsCents is a New York-based technology company passionate about transforming the laundry industry and dedicated to enabling new ways of working, earning, and living. Cents is modernizing garment care businesses by providing an all-in-one, business-in-a-box platform to help operators start, manage, and grow their businesses. By building a market-leading SaaS product for this industry, we aim to revolutionize the industry through our suite of software (Cents Point of Sale) and hardware (Pulse, Penny, and Laundroworks) products. Our team is full of passionate technology experts obsessed with supporting and empowering SMBs. We feel the unique responsibility and opportunity we have to elevate an industry. We’re adding great talent to help achieve this mission, and that’s where you come in! About The Role:As a Senior Data Analyst, you will play a key role in transforming complex data into clear, actionable insights that drive strategic business decisions across the organization. You’ll partner closely with our Chief Product Officer (CPO) and VP of Engineering as a trusted thought partner building full transparency into our product and development efforts across releases, velocity, adoption, funnels and behaviors. This role sits at the intersection of Product, Engineering, and Data: you’ll shape what we measure, how we measure it, and how leaders use those insights to make decisions. What You'll Do: Build transparency into product delivery and releases- Design and maintain reporting around product releases: scope, progress, quality signals, and post-release outcomes.- Create release-readiness and post-launch measurement frameworks (success metrics, guardrails, adoption targets).- Analyze impact of releases on customer behavior, conversion, retention, and revenue-related indicators. Measure and improve team velocity and execution health- Develop metrics and dashboards that reflect delivery health: throughput, cycle time, lead time, WIP, predictability, and bottlenecks.- Partner with Engineering and Product leaders to identify trends, root causes, and process improvements.- Establish operating rhythms that enable data driven decision making Own funnel and adoption analytics- Build and maintain product funnels, cohort analyses, and adoption dashboards for key workflows and features.- Identify drop-offs, friction points, and opportunities to improve activation and ongoing engagement.- Segment insights by persona, plan, channel, customer maturity, etc., to explain “what’s happening” and “why.” Act as a strategic thought partner to the CPO- Translate ambiguous questions into structured analyses and clear narratives.- Proactively surface risks/opportunities and recommend actions (not just findings).- Support roadmap decisions with evidence, tradeoffs, and forecasting where appropriate. Strengthen the analytics foundation- Work with data/engineering partners to ensure instrumentation is reliable and data definitions are consistent.- Define and document core metric definitions and build a “single source of truth” for product and delivery metrics.- Improve data quality through monitoring, anomaly detection, and governance.Core Qualifications • 7+ years (or equivalent) in Product Analytics, Data Analytics, or a similar role supporting Product + Engineering., • Experience working in a high growth startup, managing and improving fragmented data + building scalable models, • Deep experience turning product and engineering datasets into insights: releases, velocity, adoption, funnels., • Strong SQL skills and comfort working directly with event data, product telemetry, and engineering workflow data., • Proven ability to create metrics frameworks (North Star + supporting metrics) and keep definitions consistent., • Experience building dashboards and recurring reporting that executives actually use., • Proficiency with Looker, Fullstory, Jira, Launch Darkly and Snowflake.Engineering & delivery analytics experience, • Familiarity with Agile/modern delivery metrics and tools and concepts like cycle time, lead time, throughput, and predictability., • Strong storytelling: you can explain the “so what” clearly to executives and teams., • Comfortable pushing back, asking great questions, and aligning stakeholders around what to measure and why., • High ownership: you don’t wait for requests, you proactively surface insights and recommendations.Nice to have, • Experience with experimentation, A/B testing, and causal inference approaches., • Experience defining event tracking plans and working with engineers on instrumentation., • Comfort with lightweight forecasting models and capacity/roadmap scenario analysis.Working style & collaboration, • Working style & collaborationYou’ll work closely with the CPO, Product Managers, Engineering leaders, and Data/Analytics #LI-DNI We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.