Data Science Lead - (Geospatial AI & Climate)

DiscoverEE; Toronto; On-site; CAD 130,000 - 170,000; Full time

Job summary

Korotu Technology is seeking a Data Science Lead to guide our geospatial data initiatives and mentor co-op students. You will translate client requirements into technical workflows and own end-to-end lifecycle of data projects on our Aroa platform.

The role blends hands-on modeling with technical leadership, client delivery, and cross-functional collaboration across data scientists, software engineers, designers, and product managers.

Qualifications

• Master’s degree in a quantitative field (e.g., CS, Statistics, Geomatics, Math) or equivalent experience.
• 3+ years of data science or ML experience with geospatial data and remote sensing.
• Proven track record of leading complex data science projects from conception to delivery and client acceptance.
• Experience in leadership/mentorship and guiding junior staff.
• Strong client-facing skills with the ability to translate business problems into technical solutions.
• Expert-level Python and core data science stack (Pandas, NumPy, Scikit-learn, Keras/PyTorch).
• Excellent communication and storytelling skills for diverse audiences.

Responsibilities

• Define and drive the data science vision and roadmap for Korotu, identifying AI opportunities in natural capital.
• Act as the technical authority in client engagements and help win new business.
• Mentor and coordinate data science co-ops, promoting best practices and scalable workflows.
• Lead cross-functional teams to deliver data-driven solutions and guide productization of R&D into repeatable features on Arora.

Skills

Python

Data science

Machine learning

Leadership

Client-facing

Communication

Geospatial data

Remote sensing

Education

Master’s degree in quantitative field

Tools

Pandas

NumPy

Scikit-learn

Keras/PyTorch

Job description

Job description

Korotu Technology website can be found here: korotu.com.

About Korotu

Korotu Technology (www.korotu.com) is a fast-growing clean-tech startup on a mission to protect our planet. We use satellite imagery, AI, and on-the-ground data to help communities monitor, measure, and finance nature-based solutions. Our SaaS platform, Aroa, empowers land protectors and impact investors to fight climate change and preserve biodiversity by providing them with data they can trust. We are a small, passionate team making a big impact, working with partners like WWF-Canada and the Island Nature Trust.

The Opportunity

As our Data Science Lead, you will play a central role at Korotu. You will be responsible for guiding our data science co-op students, translating client requirements into technical workflows, and owning the end-to-end lifecycle of our geospatial projects. This role offers an exceptional opportunity to combinehands-on modeling with early-career technical leadership and client-facing project delivery. This position is a 12-month contract funded through the Green Jobs Program, structured with a clear path and intent to transition into a permanent role upon term completion.

What You'll Accomplish (Responsibilities)

Project Scoping & Business Development

• Define and drive the data science vision and roadmap for Korotu, identifying new opportunities to apply AI and machine learning to the natural capital space.
• Act as the technical authority in client engagements, working alongside the leadership team to understand client needs, shape project mandates, and win new business.
• Stay at the forefront of AI and remote sensing research, translating cutting-edge academic work into tangible commercial applications and a competitive advantage for Korotu.

Team Guidance & Co-op Mentorship

• Serve as the primary technical mentor and daily coordinator for our data science co-op students, guiding them through project onboarding, code reviews, and technical unblocking.
• Foster a collaborative environment of intellectual curiosity, best engineering practices, and peer learning within the data science stream.
• Help shape internal team workflows and documentation to ensure co-op projects scale smoothly into our core platform.

Project Execution & Productization

• Own the full project lifecycle, from initial problem discovery and prototyping to deliveringrobust, data-driven solutions to our clients.
• Lead cross-functional project teams, ensuring seamless collaboration between data scientists,software engineers, designers, and product managers.
• Partner closely with the engineering lead to architect and implement the productization ofsuccessful R&D projects, turning bespoke solutions into scalable, repeatable features on ourArora platform.

What We're Looking For (Qualifications)

We are looking for curious and analytical students who are passionate about using data to solvereal-world problems.

Funding Eligibility Criteria

Please note that this role is funded by Clean Foundation’s Green Jobs Program and therefore the successful candidate must meet the following requirements set out by the funder:

• Between the ages of 15 and 30 (inclusive) at the start of the position
• Be a Canadian Citizen, Permanent Resident, or Protected Person as defined by the Immigrationand Refugee Protection Act
• Not a student or currently enrolled in school or an academic program at the start of theemployment
• Be legally entitled to work in Canada
• Be legally entitled to work according to the relevant provincial/territorial legislation andregulations

Must-Haves

• A Master’s degree or PhD in a quantitative field (e.g., Computer Science, Statistics, Physics, Geomatics, Mathematics) or equivalent professional experience.
• 3+ years of experience in data science or machine learning. Direct experience with geospatial data (raster/vector data) and remote sensing applications.
• A proven track record of leading complex data science projects from conception through to delivery and client acceptance.
• Experience in a leadership, management, or team lead capacity, including mentoring junior staff.
• Strong client-facing skills, with experience in a consultative role where you translated ambiguous business problems into concrete technical solutions.
• Expert-level proficiency in Python and its core data science ecosystem (e.g., Pandas, NumPy, Scikit-learn, Keras/PyTorch).
• Exceptional communication and storytelling skills, with the ability to articulate complex technical concepts to both expert and non-expert audiences.

Bonus Points (Nice-to-Haves)

• Experience in a