Tech Stack

Description

You will partner with product and business leaders across marketplace teams to drive data-informed decisions, owning the product analytics roadmap for Contact Center products including AI Assistant and IVR. You will lead end-to-end measurement for AI systems, collaborate on scalable logging, design A/B and causal tests, and translate insights into strategic recommendations. You will also hire and mentor team members in AI analytics and experiment best practices.

Requirements

• Min 8 or more 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).
• Data engineering foundations, including ability to work with data engineering teams on pipeline design, metric computation jobs, data model changes, and maintaining reliable end-to-end metric systems.
• 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.

Responsibilities

• Own the product analytics roadmap, prioritisation 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 optimisations.
• Translate insights into strategic recommendations for senior leaders; shape product priorities through data.
• Hire, mentor and up-level team capability in AI analytics, experiment best practices and storytelling.