Senior Data & AI Scientist for Impactful ML in SaaS

Benevity; Vancouver; Hybrid; CAD 110,000 - 165,000; Full time

Job summary

Benevity is seeking a Senior Data and ML/AI Scientist to design and build AI-powered features for our B2B SaaS platform. You’ll work with AI engineers, product teams, and data engineers to deploy scalable models, create data-driven insights, and prototype innovative algorithms that improve customer experiences and business outcomes.

You’ll contribute to reproducible training pipelines, model validation, and monitoring dashboards, ensuring robust, production-ready solutions.

Qualifications

• 4-6 years of experience in data science, ML engineering, or applied AI roles.
• Experience building customer-facing or business-impacting models (e.g., scoring, personalization, anomaly detection).
• Familiarity with collaborative software workflows (Git, code reviews, CI/CD for ML).
• Ability to work independently while contributing in a team setting.
• Strong communication skills for both technical and non-technical audiences.
• Awareness of ethical implications of ML including fairness and explainability.

Responsibilities

• Design and develop ML models and statistical solutions to support product features.
• Perform data exploration, feature engineering, and dataset prep for training and evaluation.
• Analyze model performance and iterate based on experiments.

Skills

Python

SQL

Jupyter

Git

ML engineering

TensorFlow

PyTorch

NLP

Time-series

Education

Bachelor’s or Master’s in Data Science/CS/Statistics/Engineering

Tools

BigQuery

Snowflake

DBT

Pandas

NumPy

Docker

Kubernetes

Looker

Power BI

Job description

Benevity is seeking a Senior Data and ML/AI Scientist to design and build AI-powered features for our B2B SaaS platform. You’ll work with AI engineers, product teams, and data engineers to deploy scalable models, create data-driven insights, and prototype innovative algorithms that improve customer experiences and business outcomes.

You’ll contribute to reproducible training pipelines, model validation, and monitoring dashboards, ensuring robust, production-ready solutions.