Senior Associate - Data Analytics

deutsche telekom digital labs

4-6 Years

Gurugram, India

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Job Description

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.
Strong 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.