Applied AI Analyst

Autodesk•Toronto, ON

About The Position

The Digital Experience & Customer Empowerment Data Science (DXC-DS) team builds ML-powered experiences that transform how customers interact with Autodesk. A key focus area is the Commerce & Support Agent (CSA), an LLM-driven chatbot supporting commerce and support journeys. We’re hiring an early-career Applied AI Analyst to help deeply understand and improve CSA performance. This role sits at the intersection of product, machine learning, and business impact. It is not a traditional reporting role — it focuses on developing scalable analytical methodologies to answer meaningful questions, uncover performance drivers, and influence decisions. If you’re highly analytical, fluent in SQL and Python, and motivated by solving complex, ambiguous problems, this role is for you.

Requirements

Strong proficiency in SQL and Python (hands-on, daily use level).
Ability to work with large, complex datasets in a data warehouse environment (e.g., Snowflake, Hive, Presto).
Solid understanding of statistics and analytical thinking (hypothesis testing, structured problem solving).
Demonstrated ability to move from raw data to clear insight independently.

Nice To Haves

Familiarity with instrumentation, event tracking, or data logging systems.
Exposure to product analytics, experimentation, agentic and MCP driven systems.
Experience working cross-functionally in fast-moving environments.
Experience with Pyspark

Responsibilities

Build scalable analytics assets
Develop robust SQL-based datasets and Python workflows to support repeatable analysis.
Create analytical frameworks and reusable data products that improve decision velocity.
Collaborate with Data Ops and Engineering to ensure data is reliable and well-understood.
Work closely with instrumentation and data foundations
Develop a strong understanding of event tracking and instrumentation design.
Partner with Data Ops to validate data quality and ensure metrics reflect system reality.
Contribute to principled metric definitions and documentation.
Turn questions into insight
Partner with ML, Engineering, and Business teams to frame analytical questions clearly and rigorously.
Translate ambiguity into structured analyses and actionable findings.
Analyze chatbot and system performance
Conduct deep dives to identify performance drivers, anomalies, and opportunities for improvement.
Connect system behavior to downstream business outcomes.