Data Scientist (AI)

TL;DR

Data Scientist (AI): Building models for matching, recommendation, and ranking to connect people to jobs, skills, and pathways with an accent on applied data science and workforce taxonomies. Focus on shipping production-ready models and translating complex labor market data into actionable insights.

Location: Remote (Must be based in the US or Canada). Office available in Toronto.

Salary: USD $100,000 – $140,000 / CAD $110,000 – $155,000

Company

AI-powered platform focused on workforce development to resolve economic inequality by helping people find better jobs faster.

What you will do

• Build, evaluate, and ship matching and ranking models that directly shape the job seeker experience.
• Work with skills, occupation taxonomies, and labor market data to improve representation of the world of work.
• Collaborate with Engineering to move models into production reliably and monitor their live performance.
• Translate messy, real-world data into clear findings and recommendations for the team and customers.

Requirements

• 4+ years of applied data science experience with a track record of shipping models into real products.
• Explicit experience with jobs-and-skills or workforce data (Firm criterion).
• Fluency in Python and SQL.
• Solid grounding in machine learning, NLP, and recommendation/matching techniques.
• Ability to explain model tradeoffs to non-technical audiences.

Nice to have

• Experience with recommender systems, ranking, or search at scale.
• Familiarity with skills/occupation frameworks such as O*NET or ESCO.
• Experience pairing classical ML with LLMs and implementing guardrails.
• Public artifacts (publications, blog posts) showcasing depth of knowledge in data science.

Culture & Benefits

• High-trust, high-intensity environment focused on meaningful global impact.
• Remote-first work arrangement with travel up to once per quarter for team gatherings.
• Mission-driven culture dedicated to unlocking human potential and reducing economic inequality.

Hiring process

• Initial screen with Director of People & Culture followed by an interview with the Hiring Manager.
• Performance challenge to evaluate technical application.
• Final 1:1 interviews before the final decision.