Product Analyst

Company Description

At The Stepstone Group, we have a simple yet very important mission: The right job for everyone. Using our data, platform, and technology, we create opportunities for jobseekers and companies around the world to find a perfect match in a fair and equitable way. With over 20 brands across 30+ countries, we strive for fair and unbiased hiring.

Join our team of 3,000+ employees and be part of reshaping the labor market and becoming the world’s leading job platform.

Job Description

Join our team and you’ll be responsible for answering product and business questions with data. You will own analytical projects from data through to insight, working with your manager and stakeholders to frame the problem and agree the approach. Your work could take many forms, from dashboards and funnel analyses to tracking design and A/B test read-outs.

Working in the Product Analytics department, you will partner closely with Product Managers, Heads of Product, and cross-functional teams, helping shape product decisions through data.

We expect our analysts to work with AI, not around it. You will be encouraged to use AI tooling to move faster on the mechanical parts of analysis, while keeping full accountability for the correctness of what you produce.

By joining our team, you will play a key role in improving product performance while building the depth and judgment to take on broader, more ambiguous problems over time.

Your responsibilities:

• Partner with Product teams to define, monitor, and investigate KPIs, and deliver deep-dive analyses that explain what is driving user behavior and product performance, translating findings into clear recommendations.
• Support product discovery through opportunity sizing, hypothesis generation, and input into experiment design, then set up, run, and analyze A/B tests, explaining what results do and do not tell us.
• Own the data foundations behind your work: write and refine behavioral tracking specifications, validate that events are captured correctly across user journeys, and partner with data teams to source, transform, and validate data.
• Build and maintain dashboards and analytical outputs using tools such as Adobe Analytics, Power BI, and Python, and communicate insights to stakeholders in a way that lands, using clear visualization and data storytelling.
• Use AI tooling to raise your own leverage: generating and reviewing code, exploring unfamiliar datasets, drafting documentation, summarizing qualitative feedback at scale, and sharing what works with your peers.