Principal, Product Analytics

Synthesia is the world's leading platform for generating AI video, trusted by over 90% of Fortune 100 companies. Founded in 2017 and headquartered in London, Synthesia operates across Europe and the US with a mission to enhance how organizations communicate visually and develop their workforce through AI-powered tools. The company recently closed a Series E funding round raising $200 million, bringing total valuation to $4 billion and cumulative funding to over $530 million from premier venture investors and accomplished operators across the tech industry.

You'll join Synthesia as Principal, Product Analytics, leading the investigative core of a newly proactive data function. In this hands-on, independent role, you'll investigate complex questions about user behavior and customer experience, following the data across acquisition, activation, usage and the full customer journey. Your work will directly shape product decisions, inform experiments, guide the roadmap and influence company strategy, all while partnering with Product Managers, engineering leaders and commercial teams under the direction of a VP of Growth.

What you'll do

• Identify opportunities and problems before they're asked about by noticing signals in funnels, cohorts and metrics, then conducting deep investigations into root causes and potential product-led solutions.

• Conduct rigorous investigations into user behavior and customer experience spanning both product and non-product touchpoints such as support, customer success and sales.

• Pinpoint where user activation breaks down in the journey and uncover failure points that could become productized features.

• Analyze acquisition channels and user intent to understand what people are trying to achieve and why they choose certain options.

• Perform statistical and causal analysis using regression, causal modeling and well-designed experiments, clearly communicating what evidence supports and what it doesn't.

• Develop models that drive real business action, such as churn prediction triggering real-time product responses, with transparent explanation of model application and measurable impact.

• Work with agent-user conversations, evaluation systems and context layers alongside traditional structured product data specific to AI systems.

• Size market opportunities to support business prioritization and resource allocation.

• Collaborate with engineering managers on organizational productivity metrics.

• Translate findings into clear recommendations for product, management and executive audiences.

What you'll bring

• Substantial product analytics experience across growth and product areas, with a demonstrated track record of investigations that influenced major decisions.

• Data science and modeling expertise with clear ability to describe how you applied techniques and what business results followed.

• Strong foundation in correlation, regression and causal analysis methods.

• Proactive mindset where you surface insights and set your own agenda rather than waiting for requests.

• Natural curiosity and the discipline to investigate anomalies until you understand their causes.

• Strong communication skills that distill complex analysis into actionable insights for executives and management.

Nice to have

• Experience working with unstructured data.

• Background at an AI-native company or familiarity with the data complexities AI products introduce.

• Knowledge of subscription business models.

• Understanding of product-led growth motion in B2B markets.

• Experience on multi-product platforms where upsells, cross-sells and bundling drive revenue.

• Collaboration with qualitative research to connect data findings with underlying reasons.

• Involvement in pricing, packaging or willingness-to-pay analysis.

What they offer

• The opportunity to tackle the most challenging analytical work in the company with direct visibility into product and strategy decisions.

• Full scope across structured and unstructured data, customer conversations and AI evaluation, bridging product usage, AI and revenue.

• Principal-level autonomy and impact without management responsibilities.