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About Chargebee: Chargebee is a leading provider of billing and monetization solutions for thousands of businesses at every stage of growth — from early-stage startups to global enterprises. With our powerful suite of multi-product solutions, Chargebee helps businesses unlock unparalleled revenue growth, experiment with new offerings and monetization models, and stay globally compliant as they scale. Chargebee counts innovative companies like Zapier, Freshworks, DeepL, Condé Nast, and Pret A Manger amongst its global customer base and is proud to have been consistently recognized by customers as a Leader in Subscription Management on G2. With headquarters in North Bethesda, Maryland, our 1000+ team members work remotely throughout the world, including in India, Europe and the US. Job Summary: The Chargebee Product Analytics team provides analytical insights and solutions for critical cross-company functions and processes that affect how we show up in the world for our customers, including SaaS Billing, Retention, Customer Focus, and Payments. As a Data Scientist, you can use your quantitative skill set, empathy towards customers, and collaborative spirit to work closely with Product, Ops, Marketing, Engineering, and Finance to provide data-driven insights. In addition, it will allow you to find new opportunities to take our product and business to the next level. As a Data Scientist, you'll focus on the following: The analysis, manipulation, visualization of data, and data story-telling At times you shouldn't hesitate to do data engineering/ETL (extract-transform-load) Provide product or business insights and analytical strategy There will be an additional focus on the design and analysis of experiments, and pseudo-control techniques We've noticed that the title "Data Scientist" represents various work across the industry. If you're more passionate about building machine learning (ML) or econometric models, please check out the Machine Learning roles on our career page! Roles and Responsibilities: Refine ambiguous questions and generate new hypotheses about the product and business through a deep understanding of the data, our customers, and our business. Design experiments and interpret the results to draw detailed and impactful conclusions. Define how our teams measure success by developing Key Performance Indicators, Input /Output metrics, and other customers/business metrics in close partnership with product and other subject areas such as engineering, operations, and marketing Collaborate with data scientists, BI teams, and engineers to build and improve the availability, integrity, accuracy, and reliability of data logging/telemetry, data pipelines, and reporting insights. Develop data-driven business insights and work with cross-functional partners to identify opportunities and recommend prioritization of product, growth, retention, and optimization initiatives. Must Haves: M.S. or Bachelor's degree in Math, Economics, Statistics, Engineering, Computer Science, or other quantitative fields. (If an M.S. degree, a minimum of 2+ years of industry experience is required, and if a Bachelor's degree, a minimum of 3+ years of industry experience as a Product Analyst, Data Scientist, or equivalent) Experience in at least one scripting language (SQL, Python, R, or SAS preferred) Basic understanding of experimental design (such as A/B experiments) and statistical methods Willingness to get your hands dirty with messy data to identify product opportunities and streamline data pipeline, automate and gain efficiency. Ability to communicate effectively and manage relationships with partners coming from both technical and non-technical backgrounds Strong story-telling: Distill interesting and hard-to-find insights into a compelling, concise data story Experience with experimental design and statistical methods such as causal Inference. Strong judgment, critical thinking, and decision-making skills Ability to solve complex business problems that cross multiple product/project areas and teams Balance attention to detail with swift execution Nice to have: Advanced degrees in Math, Economics, Statistics, Engineering, Computer Science, Operation Research, Quantitative analysis, Machine Learning, or other quantitative fields. 5+ years of industry experience in consumer-facing product and data science Data Science or Product analytics experience in SaaS companies or the B2B fintech sector. Technical Skillset: SQL (Advanced) : Highly proficient in writing complex SQL queries for data extraction, manipulation, and analysis from various databases. This includes understanding different joins, subqueries, window functions, and optimization techniques. Data Analysis & Interpretation: Strong ability to collect, clean, process, analyze, and interpret large and complex datasets to identify trends, patterns, anomalies, and root causes. Statistical Analysis: Solid understanding of statistical concepts (hypothesis testing, regression, correlation, A/B testing, sampling distributions) and their application to product and business problems. Programming (Python/R): Proficiency in Python or R for data manipulation (Pandas/dplyr), statistical modeling, machine learning (scikit-learn, TensorFlow/PyTorch - depending on the data science depth), and automation of data tasks. Data Visualization : Expertise in creating clear, compelling, and actionable dashboards and reports using tools like Tableau. Ability to tell a story with data. A/B Testing & Experimentation: Experience in designing, executing, and analyzing A/B tests to measure the impact of product changes and new features. Understanding of experimental design principles. Product Analytics Tools: Familiarity with product analytics platforms (e.g., Sentry, Pendo, Google Analytics, Splunk) for tracking user behavior, engagement, and feature adoption. Business & Product Skills: Deep understanding of the B2B SaaS fintech business model, sales cycles, customer journey, and revenue drivers. Product Strategy & Roadmap: Ability to translate data insights into actionable product recommendations and contribute to product strategy and roadmap development. Market Research & Competitive Analysis: Experience in conducting market research, analyzing competitor products and strategies, and identifying market opportunities. User Experience (UX) Understanding: Ability to analyze user behavior data to identify pain points, optimize user flows, and enhance overall user experience. Problem Solving: Highly analytical and methodical approach to identifying problems, breaking them down, and developing data-driven solutions. Soft Skills: Logical Thinking : Exceptional ability to think critically, identify underlying issues, and construct sound arguments based on data. Stakeholder Management : Proven ability to effectively communicate with and manage expectations of diverse stakeholders (product managers, engineers, sales, marketing, leadership). This includes translating complex technical findings into understandable business insights. Communication (Verbal & Written) : Excellent presentation skills, ability to articulate complex concepts clearly and concisely to both technical and non-technical audiences. Strong documentation skills. Collaboration : Ability to work effectively in cross-functional teams, fostering a collaborative environment. Proactive & Curious : A self-starter with a strong sense of curiosity, a desire to dig deeper into data, and a proactive approach to identifying opportunities. Adaptability : Ability to thrive in a fast-paced, dynamic B2B SaaS environment and adapt to evolving priorities. We are Globally Local With a diverse team across four continents, and customers in over 60 countries, you get to work closely with a global perspective right from your own neighborhood. We value Curiosity We believe the next great idea might just be around the corner. Perhaps it’s that random thought you had ten minutes ago. We believe in creating an ecosystem that fosters a desire to seek out hard questions, and then figure out answers to them. Customer! Customer! Customer! Everything we do is driven towards enabling our customers’ growth. This means no matter what you do, you will always be adding real value to a real business problem. It’s a lot of responsibility, but also a lot of fun. Show more Show less
