Location: Mississauga, ON-Hybrid (3 days on-site are mandatory) Contract Length: 6 Months

We at Raise are hiring a Data Scientist for one of our top clients. After establishing themselves as an industry leader, they’re now expanding their team to meet rising demand. We’re hiring right now; if you’re interested, apply below for your chance to join a great place to work.

Responsibilities

The Senior Data Scientist is expected to perform the following responsibilities:

Own analytical workstreams end to end, from data to validated, decision-ready outputs. Validate operational data and define clear, defensible data foundations before modelling. Build transparent baselines before advanced models and justify any added complexity. Apply statistical, time-series, machine learning, and optimization methods as appropriate. Validate models against real operational conditions and communicate performance honestly. Translate model outputs into recommendations stakeholders can act on with confidence. Partner with Data Engineering, Business Intelligence, Operations, and MLOps / ML engineering. Produce production-readiness artifacts and support clean handoff to deployment and monitoring. Communicate uncertainty and limitations clearly, and identify when an output is not ready for operational use.

Required Experience

Candidates are required to demonstrate the following experience: Five or more years in data science, forecasting, operations analytics, or applied machine learning. Strong Python and SQL. Time-series, regression, gradient boosting, or statistical modelling experience. Demonstrated ability to work from messy operational data to trusted, validated outputs. Ability to explain model performance and limitations to technical and business stakeholders. Evidence of owning work through to handoff or production, not only exploratory analysis.

Preferred Experience

The following experience is considered an asset: Airport, airline, transit, logistics, or other complex operations experience. Forecasting, queueing, simulation, or optimization methods. Microsoft Fabric, Power BI, Azure Machine Learning (Azure ML), MLflow, and Git. Model governance: versioning, validation, monitoring, and retraining practices. Experience designing decision-support or recommendation outputs.

Success Measures

Performance in the role is measured against the following outcomes:

Models are accurate, explainable, and trusted by operational and business stakeholders. Performance is validated against real operational conditions, not only average accuracy. Outputs are reconciled, supportable, and ready for production handoff. Work is handed to ML engineering with complete artifacts and minimal rework. The two scientists provide mutual coverage and a consistent quality bar across workstreams.

Looking for meaningful work? We can help!

Raise is an established hiring firm with over 65 years of experience. We believe strongly in making the world a better place through work, which is why we’re a certified B Corporation and donate 10% of our profits to charity.

We strive to build teams that reflect the diversity of the communities we work in. We encourage all qualified applicants to apply, including people from traditionally underrepresented groups such as women, visible minorities, Indigenous peoples, people identifying as LGBTQ2SI, veterans, and people with visible/nonvisible disabilities.

We have a dedicated webpage for accommodations where you can learn more about what we offer, and request accommodation: https://raise.jobs/accommodations/

In order to submit candidates for roles, our clients will sometimes require personal information to confirm the identity of applicants and their legal status to work. Raise will never ask you for personal or banking information unless you have been selected for a job. If you are ever unsure about the legitimacy of this or another job posting by Raise (or have any other questions), please contact us at +1 800-567-9675 or hello@raiserecruiting.com

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