Senior Data and AI Scientist
Benevity
Toronto, Canada · Posted today · 25 Sept 2026
City
Toronto
Type
Full-time
Field
Other
Pay
On apply page
Compensation: CA$109,400 – CA$150,370
Overview
Compensation: CA$109,400 – CA$150,370
MEET BENEVITY
Benevity is the way the world does good, providing companies (and their employees) with technology to take social action on the issues they care about. Through giving, volunteering, grantmaking, employee resource groups and micro-actions, we help most of the Fortune 100 brands build better cultures and use their power for good. We’re also one of the first B Corporations in Canada, meaning we’re as committed to purpose as we are to profits. We have people working all over the world, including Canada, Spain, Switzerland, the United Kingdom, the United States and more!
We are looking for a curious, analytical, and technically strong Senior Data and ML/AI Scientist to help design and build AI-powered solutions that enhance our B2B SaaS platform. As an individual contributor, you will develop machine learning models, data-driven insights, and AI prototypes that directly impact customer experience, automation, and business outcomes.
In this role, you will work alongside AI engineers, product teams, and data engineers to bring intelligent features to life—leveraging industry-leading tools and frameworks to ensure models are accurate, scalable, and production-ready.
What you’ll do
- Design and develop machine learning and statistical models to support product features such as recommendations, predictions, or classification.
- Conduct data exploration, feature engineering, and preprocessing to prepare datasets for model training and evaluation.
- Analyze model performance using appropriate metrics and iterate based on experimentation.
- Collaborate with data analysts and product stakeholders to understand use cases and define success criteria.
- Prototype and benchmark novel algorithms in areas such as NLP, representation learning, and time-series forecasting.
- Generate actionable insights using advanced analytics, segmentation, and statistical analysis.
- Communicate findings and model outcomes to cross-functional teams in a clear and concise manner.
- Contribute to A/B testing and model validation efforts to ensure measurable impact.
- Develop dashboards or monitoring tools to track model health and business KPIs post-deployment.
- Work closely with product and AI engineering teams to deploy models into production environments, ensuring integration with backend services and APIs.
- Develop reproducible training pipelines and notebooks that adhere to versioning and documentation standards.
- Contribute to building reusable model components and feature stores that support scalable development.
- Stay up to date with advancements in the data and ML/AI ecosystem and explore new tools and frameworks
- Contribute to documentation and internal tooling that improve team efficiency and transparency
- 4–6 years of experience in data science, ML engineering, or applied AI roles, ideally within a SaaS or tech product environment.
- Experience building customer-facing or business-impacting models (e.g., scoring, personalization, anomaly detection).
- Familiarity with collaborative software development workflows (e.g., Git, code reviews, CI/CD for ML).
- Ability to work independently on tasks while contributing effectively in team settings.
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field.
- Strong communication skills with the ability to explain complex technical topics to both technical and non-technical audiences.
- Demonstrated awareness of ethical implications of ML models, including fairness, bias, and explainability in AI.
- Experience designing or evaluating models for robustness, interpretability, and inclusivity is a plus.
- Languages & Tools: Python, SQL, Jupyter, Git
- ML Frameworks: scikit-learn, XGBoost, LightGBM, TensorFlow or PyTorch (basic)
- Data Too
Model Development & Analysis
Insights & Decision Support
Collaboration & Technical Growth
What you’ll bring:
Technical Skills & Expertise:
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