Permanent, full-time, 4 days per week in office

Connecting clients to markets – and talent to opportunity

With 5,400+ employees and over 80,000 institutional, commercial, and payments clients, we operate from more than 80 offices spread across six continents. As a Fortune 100, Nasdaq-listed provider, we connect clients to the global markets – focusing on innovation, human connection, and providing world-class products and services to all types of investors.

Whether you want to forge a career connecting our retail clients to potential trading opportunities, or ingrain yourself in the world of institutional investing, StoneX Group is made up of four business segments that offer endless potential for progression and growth.

Business Segment Overview: Engage in a deep variety of business-critical activities that keep our company running efficiently. From strategic marketing and financial management to human resources and operational oversight, you’ll have the opportunity to optimize processes and implement game-changing policies.

Position Purpose: We are looking for an AI-forward, data-driven, and product-minded Product Data Analyst to join our international team. In this role, you will turn complex, multi-source data into actionable insights that drive meaningful product improvements and better user experiences.

AI is central to how we work. We expect every new hire to actively embrace AI as a cornerstone of their daily workflow, using it responsibly to accelerate analysis, automate repetitive work, surface patterns, improve decision-making, and raise the quality of product insights.

You will work within a large-scale data ecosystem, connecting data from multiple sources across our product portfolio, automating KPI monitoring and alerting, and partnering closely with UX Researchers, UX Designers, Product Managers, Developers, and business stakeholders to deliver a superior user experience.

This is a mid-level position that requires a proven track record in international organizations with mature data environments and a strong appetite for applying AI to modern product analytics.

Primary duties will include: 

• Connect, blend, and analyze data from multiple sources, including product events, CRM, data warehouses, third-party tools, session replay platforms, and customer feedback systems, to build a holistic view of user behavior and product performance.
• Use AI as a core part of the analytics workflow, including AI-assisted querying, data summarization, pattern detection, anomaly identification, report generation, and insight synthesis.
• Proactively identify opportunities to use AI, automation, and agentic workflows to reduce manual reporting, improve time-to-insight, and help product teams make faster, better decisions.
• Own the implementation and optimization of product analytics instrumentation across tools such as Mixpanel, Pendo, Amplitude, GA4, Hotjar, Contentsquare, and similar platforms.
• Build and maintain self-serve dashboards, AI-assisted reports, and interactive analytics views that give product teams real-time visibility into feature adoption, retention, funnels, cohorts, and user journeys.
• Implement and maintain quantitative product metrics and conversion tracking aligned with user journeys, business OKRs, and product strategy.
• Design automated alerting systems to detect KPI deviations, behavioral anomalies, adoption shifts, and funnel drop-offs before risks escalate.
• Conduct deep-dive behavioral analyses, including funnel analysis, time-to-value, cohort retention, feature stickiness, segmentation, and experimentation analysis.
• Partner with Data Engineers to ensure data integrity, govern event schemas, improve pipeline quality, and support trusted, AI-ready data foundations.
• Combine quantitative analytics with qualitative signals, including session replays, UX research findings, support feedback, and customer interviews, to create a full picture of user needs and product friction.
• Apply responsible AI practices, including validation of AI-generated outputs, protection of confidential data, bias awareness, and appropriate use of approved company tools.

To land this role you will need: 

• 4–6 years of experience in a Product Analyst, Data Analyst, Product Data Analyst, or similar role within international organizations.
• Demonstrated experience working in a large data ecosystem, connecting and analyzing data from multiple heterogeneous sources.
• Strong commitment to using AI as a regular and meaningful part of day-to-day work. Candidates must be curious, hands-on, and proactive in applying AI to improve productivity, insight quality, and decision-making.
• Applied experience using AI tools such as LLMs, Copilot, Claude, ChatGPT, notebook assistants, generative AI tools, or agentic AI workflows to accelerate data analysis, summarization, reporting, and pattern detection.
• Ability to critically evaluate AI-generated outputs, validate findings, refine prompts, and apply strong human judgment before sharing conclusions.
• Proven track record of delivering insights and product improvements in a fast-paced, cross-functional environment.
• Background in SaaS, fintech, e-commerce, or similarly data-intensive industries is strongly preferred.
• Strong SQL proficiency and working knowledge of Python.
• Proven experience implementing, analyzing, and managing product analytics platforms such as Mixpanel, Pendo, GA4, Hotjar, Contentsquare, DataDog, or similar tools.
• Deep understanding of user behavioral analytics, customer journey mapping, funnel analysis, retention analysis, and product metrics.
• Ability to design and interpret A/B and multivariate tests, including hypothesis generation and post-test statistical evaluation.
• Familiarity with UX Research methods and experience connecting qualitative user insights with quantitative data.
• Strong understanding of product metrics frameworks such as AARRR, HEART, and North Star Metric.
• Excellent collaboration skills, particularly with Product, PMO, Developers, UX, Data, and business stakeholders.
• Strong communication skills for both technical and non-technical audiences.
• Professional-level English proficiency, written and spoken.

Nice to Have:

• Experience building AI-assisted dashboards, automated insight generation, or analytics agents.
• Familiarity with session replay or behavioral heatmap tools such as Hotjar, FullStory, or Contentsquare.
• Knowledge of CDP architectures and CRM platforms.
• Experience with DataDog, GA4, or similar monitoring and web analytics platforms.
• Exposure to data governance and data quality frameworks in enterprise environments.
• Knowledge of Databricks or modern lakehouse environments.
• Experience with semantic layers, metrics stores, or analytics engineering workflows.

Working environment:

• Permanent, full-time, 4 days per week in office.

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