Responsibilities:
- Work as part of a small Customer Success Insights and Operations team that leads data analysis, predictive insights and operational support to a growing CS team dedicated to the success of our customers.
- Deliver actionable analyses and insights across key Enterprise CS OKRs, initiatives and growth experiments - leading 2-3 strategic projects per Quarter. These projects could be anything from churn analysis, expansion-likelihood modelling, behaviour clustering, to NPS sentiment and customer success plan performance.
- Build, test and maintain predictive and statistical data models that identify risk, quantify revenue opportunities and prioritise CS actions at scale.
- Support the creation of dashboards with our BI team that track customer health, renewal risk, and engagement impact across our enterprise accounts.
- Design and analyse growth and expansion experiments to identify and scale opportunities for product adoption and usage expansion.
- Partner with CS leadership to support MBRs/QBRs, operational reviews, and executive reporting.
- Drive cross-functional collaboration with Product, Sales, and Marketing to ensure alignment on customer insights and opportunity areas.
- Respond to specific internal CS requests to support customer retention and growth plays, delivering 5+ high-value analyses monthly that fuel CS OKRs and strategic decision-making.
- Leverage statistical and analytical tools (e.g., SQL, Python, statistical / ML libraries as well as BI tools like Qlik) to model data, test hypotheses, and communicate recommendations with clarity and impact.
- Explore and help operationalise the use of AI-tools like ChatGPT and Google Gemini to support analysis velocity, identify patterns and automate insights generation.
- Champion data quality and governance, ensuring reliable and scalable data pipelines in partnership with MIS and Data Engineering teams.
- Advise on KPI design and performance tracking for Enterprise CS metrics including NRR, GRR, churn, and adoption health scores.
About You:
- 3-5 years of experience in a data analyst, data science or insights role, ideally within a Customer Success, Revenue Operations, or Product Analytics function in a SaaS environment or similar data-rich organisation.
- Strong analytical and quantitative skills with a demonstrated ability to translate complex data into clear business recommendations.
- Proven expertise in SQL, Python, data modelling, and visualisation tools and building datasets for consumption at scale.
- Experience working cross-functionally to support executive reporting, churn prevention, and revenue insights.
- Familiarity with Customer Success metrics and workflows (e.g., NRR, CSAT, NPS, CLTV).
- Strong business acumen and ability to communicate insights to senior leadership clearly and persuasively.
- Experience designing or analysing controlled experiments (A/B tests) to measure the impact of CS initiatives.
- Comfortable working autonomously in a high-growth, fast-paced environment.
- Excellent written and spoken English.
Top Skills
What We Do
Cloudinary’s mission is to empower companies to deliver visual experiences that inspire and connect by unleashing the full potential of their media. With more than 50 billion assets under management and 7,500 customers worldwide, Cloudinary is the industry standard for developers, creators and marketers looking to upload, store, transform, manage, and deliver images and videos online. As a result, leading brands like Atlassian, Bleacher Report, Grubhub, Hinge, NBC, Mediavine, Peloton, Petco and Under Armour are seeing significant business value in using Cloudinary, including faster time to market, higher user satisfaction, and increased engagement and conversions. For more information, visit www.cloudinary.com.







