Product Data Scientist - AI & Analytics
Quintessential Design4+ yrsHyderabadOn-siteDirect career pageEst. 10–18 LPA
Posted 1d ago
Reach people at Quintessential Design
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Quintessential Design you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Own end-to-end product analytics: tracking plans, event taxonomy, Amplitude instrumentation, data pipelines, and metrics layer.
- Build real-time dashboards and conduct analytics (funnels, cohorts, retention, A/B testing) to inform product and marketing decisions, including predictive modeling for churn and conversion.
- Design, build, and ship AI-powered features and agents that integrate with real data and tools, running reliably in production environments.
Minimum Requirements
- 4+ years experience in product analytics, data science, or analytics engineering, preferably in a product-led company.
- Proven ownership of product instrumentation using Amplitude, Mixpanel, or similar tools.
- Strong SQL and Python skills; experience with cloud data warehouses like BigQuery, Snowflake, Redshift, or Postgres.
- Hands-on experience building and shipping at least one LLM-powered feature or agent using LLM APIs (Anthropic, OpenAI or similar) and agent frameworks/protocols like MCP, LangGraph, or Claude Agent SDK.
Ideal Candidate Profile
- Experienced in full-stack product analytics with strong execution ownership from tracking to predictive models and dashboards.
- Proficient in AI/LLM integration to build practical, production-ready customer-facing features and automation.
- Comfortable working cross-functionally with product, engineering, marketing, and leadership in a fast-moving, hardware and AI hybrid environment.