Support AI and analytics initiatives through exploratory data analysis (EDA), statistical analysis, data wrangling, and practical application of low-code/no-code generative AI tools to improve IT business processes
Work closely with Data Scientists, AI Engineers, business stakeholders, and process owners to prepare high-quality datasets, uncover insights, validate assumptions, and identify opportunities to automate, simplify, and accelerate work
Extract, join, and transform data from multiple sources using SQL and/or data tools
Clean and preprocess structured and semi-structured data
Build and maintain analysis-ready datasets to support feature engineering, model development, and business reporting needs
Apply data quality checks and document findings
Perform EDA to understand data structure, relationships, distributions, anomalies, and business context
Create visualizations and summaries to communicate insights
Conduct descriptive and basic inferential statistical analyses and assist in measurement design and KPI definition
Use low-code/no-code GenAI tools to improve efficiency, speed, and quality in IT business processes
Design and implement GenAI-enabled solutions, create prompts, reusable workflows, and lightweight AI assistants
Work in technical teams focused on analytics solutions and maintain well-structured documentation

Bachelor’s degree (or equivalent practical experience) in a quantitative or technical field such as Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, Information Systems, or similar
0-3 years of relevant work experience
Familiarity with SQL for querying and manipulating data, including joins, aggregations, and filters
Working knowledge of Python for data analysis, such as pandas/tidyverse and basic scripting
Understanding of foundational statistics including distributions, summary statistics, correlation, and basic hypothesis testing concepts
Strong attention to detail and comfort working with messy, incomplete, or evolving datasets and business requirements
Experience with data visualization tools such as Tableau or Power BI and/or Python visualization libraries
Demonstrated interest in applying generative AI tools to business workflows and process improvement
Hands-on familiarity with one or more enterprise GenAI platforms or adjacent workflow tools is preferred, including Microsoft 365 Copilot, Copilot Studio, Power Automate, ChatGPT Enterprise, custom GPTs, Claude, or similar solutions
Exposure to cloud platforms such as AWS or Azure is a plus
Familiarity with ML/AI concepts including features, labels, training versus inference data, and evaluation metrics is preferred.
Experience using Git and writing reproducible notebooks, documentation, or workflow playbooks is a plus

Data Analyst, GenAI Specialist – Enterprise AI

Key skills