Senior/Lead AI Data Analyst (AI Engineering)

TL;DR

Senior/Lead AI Data Analyst (AI Engineering): Transforming complex internal and external datasets into dashboards, statistical analyses, and actionable recommendations with an accent on SQL, experimentation, and AI-assisted analytics. Focus on building repeatable data workflows, evaluating business and product metrics, and enabling analysts across hirify.global to use AI tools effectively.

Location: Work from home in Canada

Company

hirify.global is a global analytics software company that develops data-driven solutions for credit scoring, fraud detection, lending, and business decision-making.

What you will do

• Gather, clean, validate, and analyze data from internal and external sources using AI-assisted preparation and quality-checking tools.
• Build and maintain dashboards, reports, and visualizations for business and product performance.
• Partner with product managers, data scientists, and engineers to define analyses and communicate actionable recommendations.
• Conduct exploratory analysis, statistical testing, and A/B test design and evaluation.
• Write and optimize SQL queries across large datasets and develop documented, repeatable analytics workflows.
• Champion responsible AI adoption by sharing prompting techniques, best practices, and practical guidance with analysts and other teams.

Requirements

• 7+ years of experience in data analysis, business analysis, or a similar analytical role.
• Strong SQL skills and hands-on experience with Python or R for data manipulation and statistical analysis.
• Experience with Tableau, Power BI, or Looker, plus knowledge of statistics, hypothesis testing, and experimental design.
• Practical experience with LLM assistants, AI coding copilots, or AI-powered analytics platforms.
• Experience with large or complex datasets, relational databases, and preferably cloud or big-data platforms such as AWS, GCP, Azure, Snowflake, or BigQuery.
• Bachelor’s degree in a quantitative field is required; strong communication, problem-solving, and coaching skills are also expected.

Nice to have

• Financial services, technology, or another data-intensive industry experience.
• Exposure to machine learning concepts, prompt engineering, or collaboration with data science and AI engineering teams.
• Advanced degree in a quantitative discipline.

Culture & Benefits

• Inclusive, people-first work environment guided by ownership, customer focus, and respect.
• Professional development through learning experiences and opportunities to apply individual strengths.
• Competitive compensation, benefits, and rewards programs.
• Work-life balance, employee resource groups, and social events.