Senior Data Analyst, Product Analytics

As a Senior Data Analyst at Thomson Reuters, you will play a crucial role in shaping the analytics strategy for products used by millions worldwide. Your primary responsibility will be to lead product analytics and guide teams through the AI transformation journey. Here's what the role entails: Role Overview: In this role, you will deliver strategic insights, define measurement frameworks, and evaluate AI-specific metrics such as model performance, prompt effectiveness, response quality, and user trust. Your analysis will focus on user interactions with conversational interfaces, retrieval accuracy in RAG systems, and engagement with AI features to determine business impact. Collaboration with product, engineering, and design teams will be key to owning analytics implementation and translating complex AI behaviors into actionable insights. Key Responsibilities: - Partner with developers/platform architects to deploy relevant product analytics solutions like Pendo and ensure capturing the right metrics, journeys, and events. - Utilize product analytics/data to recognize patterns and trends, understand user behavior, and identify improvement opportunities. - Proactively establish measurement frameworks/success metrics for new product launches/features and drive actionability through data-driven insights. - Apply AI-native analytics approaches, leveraging tools such as LLMs, RAG-based retrieval concepts, and GenAI tools to automate reporting and surface insights. - Independently develop and manage relationships with peers/product managers/senior leadership for collaborative partnership and driving analytical insights. - Partner with product teams to define and maintain support processes, instilling a data-driven culture within the organization. - Collaborate with BI teams and other analysts to build dashboards and reports for page performance, feature usage, and customer segments. - Demonstrate thought leadership by leveraging analyses, understanding products, deriving insights, running experiments, and addressing any analytics needs. Qualifications Required: - 5 years of hands-on product analytics experience, including working with stakeholders and driving data-driven decision-making. - Proficiency in SQL, dashboarding techniques, and statistical packages within Python/R. - Strong understanding of statistical concepts and AI tools for analytics. - Excellent people skills and stakeholder management abilities. - Exposure to product analytics tools like Pendo, Amplitude, Adobe Analytics, and Google Analytics is preferred. - SaaS experience is an asset. This opportunity offers a hybrid work model, flexibility, career development, industry competitive benefits, and a supportive workplace culture that values inclusion, work-life balance, and social impact. Thomson Reuters is committed to diversity and equal employment opportunities for all qualified individuals. Join us in shaping the industries that move society forward. As a Senior Data Analyst at Thomson Reuters, you will play a crucial role in shaping the analytics strategy for products used by millions worldwide. Your primary responsibility will be to lead product analytics and guide teams through the AI transformation journey. Here's what the role entails: Role Overview: In this role, you will deliver strategic insights, define measurement frameworks, and evaluate AI-specific metrics such as model performance, prompt effectiveness, response quality, and user trust. Your analysis will focus on user interactions with conversational interfaces, retrieval accuracy in RAG systems, and engagement with AI features to determine business impact. Collaboration with product, engineering, and design teams will be key to owning analytics implementation and translating complex AI behaviors into actionable insights. Key Responsibilities: - Partner with developers/platform architects to deploy relevant product analytics solutions like Pendo and ensure capturing the right metrics, journeys, and events. - Utilize product analytics/data to recognize patterns and trends, understand user behavior, and identify improvement opportunities. - Proactively establish measurement frameworks/success metrics for new product launches/features and drive actionability through data-driven insights. - Apply AI-native analytics approaches, leveraging tools such as LLMs, RAG-based retrieval concepts, and GenAI tools to automate reporting and surface insights. - Independently develop and manage relationships with peers/product managers/senior leadership for collaborative partnership and driving analytical insights. - Partner with product teams to define and maintain support processes, instilling a data-driven culture within the organization. - Collaborate with BI teams and other analysts to build dashboards and reports for page performance, feature usage, and customer segments. - Demonstrate thought leadership by leveraging analyses, understanding products, deriving insig