Data Scientist

Our Mission

We're dedicated to helping more people get to better jobs faster and cheaper, focusing on those facing barriers to opportunity. Our AI-powered platform improves workforce development, resolving economic inequality.

Who We Are Looking For

We're seeking a Data Scientist to join our team. You will build models that directly shape the job seeker experience, working with skills and occupation taxonomies, labor market data, and matching and recommendation systems.

What You Will Own

• Applied Modelling: Build, evaluate, and ship models for matching, recommendation, and ranking that directly shape the job seeker experience.
• Skills and Jobs Data: Work with skills, occupation, and career taxonomies and labor market data, improving how we represent and reason about the world of work.
• Production Partnership: Collaborate with Engineering to move models into production reliably, and monitor and improve them once they are live.
• Clear Analysis: Translate messy, real-world data into clear findings and recommendations that the team and our customers can act on.

Required Experience

• Strong applied data science experience (roughly 4+ years), with a track record of shipping models that made it into a real product
• Explicit jobs-and-skills or workforce data experience, OR experience with closely related data where there is a clear pathway to apply it to workforce problems
• Fluency in Python and SQL, and solid grounding in machine learning, NLP, and recommendation/matching techniques
• Comfort working with large, imperfect datasets and making sound judgment calls about them
• Clear communication: you can explain a model and its tradeoffs to a non-technical audience

Bonus Points

• Experience with recommender systems, ranking, or search at scale
• Familiarity with skills/occupation frameworks (e.g. O*NET, ESCO) or HR/labor market data
• Experience pairing classical ML with LLMs, including where to use each and how to add guardrails
• Publications, presentations, blog posts, or other public artifacts showcasing your expertise and depth of knowledge in data science

Our Tech Stack for Data

• Languages: Python, SQL
• Machine learning and NLP: scikit-learn, modern NLP and embedding tooling, AWS SageMaker
• Data orchestration and transformation: Airflow, dbt
• Data storage and warehousing: PostgreSQL, Redshift, MongoDB
• Visualization and reporting: Looker

Education

Your grit, hunger, and drive are what matter most. Learn continuously, tackle challenges head-on, and know your strengths and gaps intimately.

Location

We are open to candidates living anywhere in Canada or the US. For candidates living in Toronto, our office is conveniently located at 325 Front St West (a short walk from Union Station).

Travel Expectations

Although this role is remote, you may be expected to travel up to once per quarter for offsites and team gatherings.

Compensation

The base salary range for this role is USD $100,000 to $140,000 for candidates based in New York and CAD $110,000 to $155,000 for candidates based in Toronto, benchmarked to the middle of the market for comparable venture-backed companies.

Hiring Journey

At FutureFit AI, our hiring process is designed to help you assess whether this role and our culture are the right fit based on your unique skills, mindset, and experiences. We move fast and work with intensity, so we want you to get a real sense of that from the start. Each journey includes a mix of interviews and a performance challenge. For this role, that might look like:

• Online Application
• Initial Screen with Director of People & Culture
• Interview with Hiring Manager
• Performance Challenge
• Final 1:1 Interviews
• Final Decision

Company Snapshot

Team: 30-50 across US and Canada (hubs in NYC and Toronto)

Customers: Workforce development agencies and intermediaries, government agencies, employers

Industry: SaaS/AI technology

Funding: Bootstrapped 0-1, then raised funding led by JP Morgan

Structure: Growth, Customer Success, Product, Engineering, Data, People & Culture, Finance & Operations

Core Principles

• Be Curious
• Drive to Outcomes
• Raise the Bar
• Speed Matters
• Own It
• We Over Me

Use of AI in Hiring

• Screening support: AI may help us compare applications against the skills and experience required for a specific role. These skills are defined by the hiring team for each position. A human reviews each application, with the AI assessment as just one input.
• Interview support: In some interviews, we may use an AI notetaker to summarize the discussion so interviewers can focus on being present in the conversation.
• Insights, not decisions: AI provides data points to support our team’s evaluation but does not make or recommend final hiring decisions. Every hiring decision is made by people.

Equal Opportunity Statement

We are proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, religion, color, gender identity, sexual orientation, age, disability, veteran status, or other applicable legally protected characteristics. We encourage people of different backgrounds, experiences, abilities, and perspectives to apply.