Data thought partner to product and business leaders across marketplace teams through providing insights, recommendations, and enabling data informed decisions.
Drive day to day product analytics and build scalable analytical solutions
Develop a deep understanding of how guests and hosts interact with our CS products including but not limited to AI Assistant, IVR and other agent assisting tools to improve the customer experience.
A Typical Day:
Owning the product analytics roadmap, prioritization & delivery of solutions in the Contact Center Product space.
Own projects from start to end: building out timelines, key milestones, providing regular updates to product managers, analytics management and delivery against agreed timelines.
Lead end-to-end measurement for AI systems, aligning metrics with business outcomes, user experience, and trustworthiness
Collaborate with engineering to define scalable logging and ensure observability across agentic and LLM workflows.
Lead the design and evaluate A/B and causal tests to quantify impact of AI features and optimizations.
Translate insights into strategic recommendations for senior leaders; shape product priorities through data.
Your Expertise:
12+ years in industry experience and a degree (Masters or PhD is a plus) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research).
Expert communication and collaboration skills with the ability to work effectively with internal teams in a cross-cultural and cross-functional environment. Ability to conduct rigorous analysis and communicate conclusions to both technical and non-technical audiences
Strong expertise in Python, SQL, A/B testing platforms and best practices
Expertise in EDA, hypothesis testing, significance testing, regression, clustering techniques, concepts of NLP/Text Mining, machine learning and deep learning techniques, language model fine-tuning etc
Understanding of LLM architectures (e.g., prompt chains, retrieval augmentation, orchestration frameworks like LangChain or DSPy).
Familiarity with Agentic AI systems, human-in-the-loop design, and AI observability best practices
Experience partnering with internal teams to drive action and providing expertise and direction on analytics, data science, experimental design, and measurement.
Experience designing and building metrics, from conception to building prototypes with data pipelines
Familiarity with vector stores, embeddings, prompt instrumentation, and structured logging of LLM interactions would be a plus
Contact center domain and market place domain knowledge would be a plus