Key Responsibilities

- Own analytics for AI-powered products such as conversational bots, LLM-based features, service automation journeys, tagging systems, and customer AI experiences.

- Define, track, and improve key product metrics including adoption, engagement, containment, resolution rate, escalation rate, fallback rate, user satisfaction, journey completion, and repeat interactions.

- Write advanced SQL queries to analyze large-scale product, customer, event, bot, and interaction-level datasets.

- Build robust data models and reusable analytical datasets to support dashboards, reporting, experimentation, and product deep dives.

- Use Python for exploratory analysis, automation, data validation, statistical analysis, and conversation/text-level analysis.

- Analyze conversational journeys to identify user intent patterns, unresolved queries, drop-offs, fallback behavior, escalation drivers, tagging gaps, and customer pain points.

- Conduct deep-dive analyses to explain KPI movements, product performance changes, customer behavior trends, and business impact.

- Design and maintain dashboards and reports using BI tools such as Metabase, Tableau, Power BI, Looker, or similar platforms.

- Partner with Product, Engineering, Data, Design, and Business teams to convert business questions into analytical frameworks and measurable outcomes.

- Support experimentation and impact measurement for AI product features, chatbot flows, tagging improvements, and LLM-powered capabilities.

- Present insights through clear storytelling, visualizations, and structured recommendations for both technical and non-technical stakeholders.

- Contribute to analytics best practices, KPI definitions,



metric documentation, dashboard standards, and data quality frameworks.

- Mentor junior analysts and support the team in building strong analytical problem-solving capabilities.

Required Skills And Qualifications

- 4–5+ years of relevant experience in data analytics, product analytics, business analytics, or digital product analytics.

- Strong hands-on experience with SQL, including joins, CTEs, window functions, aggregations, funnel analysis, cohort analysis, and query optimization.

- Proficiency in Python or R, preferably Python, for data analysis, automation, statistical analysis, and visualization.

- Robust understanding of data modeling, KPI design, metric definitions, and analytical frameworks.

- Experience working with large-scale datasets, event data, customer interaction logs, data warehouses, or cloud data platforms.

- Experience with BI and visualization tools such as Metabase, Tableau, Power BI, Looker, or equivalent.

- Good understanding of statistics, including hypothesis testing, experiment design, confidence intervals, correlation, regression basics, and predictive techniques.

- Ability to perform structured deep dives, root-cause analysis, segmentation, trend analysis, and performance diagnostics.

- Excellent communication and storytelling skills, with the ability to simplify complex analysis into clear business insights.

- Strong stakeholder management skills with experience working across Product, Engineering, Business, and Data teams.

- Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field, or equivalent practical experience.

📌 Senior Associate - Data Analytics (Gurugram)
🏢 Deutsche Telekom Digital Labs
📍 Gurugram