Closed listing
Data Scientist
- Toronto, ON, Canada
Contract
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Contract
- Closing date
- Experience
- Master's degree in a relevant quantitative/technical discipline with 4+ years analytical/data science experience.
- Posting language
- English
- Posted
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Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
Title: Data Scientist – AI/ML
Location: Canada (hybrid role requiring 3 days per week in the Toronto, Canada)
Type: Contract
Start Date: Immediate
Must Have:
Python + Advanced AI/ML + Cloud (AWS/GCP/Azure) + SQL/Snowflake + ML Deployment/MLOps + Production Software Development + Business Communication
The candidate should be a hands-on Data Scientist, not purely an academic/research profile, with demonstrated experience taking AI/ML models from data → modeling → development → deployment → production.
Role Overview
We are seeking a hands-on Data Scientist with strong expertise in AI/ML modeling, Python, cloud platforms, and production-ready AI solutions. The candidate will develop and deploy advanced machine learning solutions, work with complex datasets, and collaborate with business and technical stakeholders in an agile environment.
Top Skills Required
AI/ML Modeling: Strong hands-on experience with supervised/unsupervised learning, deep learning, time-series forecasting, Bayesian statistics, optimization, and other advanced ML techniques.
Python: Expert-level Python development with experience building reusable functions, classes, libraries, and production-quality code.
ML Engineering / MLOps: Experience taking models from development to production, including CI/CD, orchestration, deployment, testing, and version control.
Cloud & Big Data: Hands-on experience with AWS, GCP, or Azure and technologies such as Databricks and Apache Spark.
Data Platforms: Strong SQL skills with experience in Snowflake and relational/NoSQL databases.
AI Product Development: Experience developing AI/ML solutions within an agile, product-focused environment.
Business Communication: Ability to translate complex data science concepts into clear business language and communicate insights through data visualization and storytelling.
APIs & Software Development: Experience working with enterprise APIs and production software development practices.
Visualization: Experience with Tableau, Power BI, or Plotly.
Version Control: Strong experience with Git or equivalent tools.
Education & Experience
PhD in Computer Science, Mathematics, Statistics, Physics, or related quantitative discipline with 2+ yearsanalytical/data science experience; OR
Master's degree in a relevant quantitative/technical discipline with 4+ years analytical/data science experience.
More about this job
Responsibilities
Develop and deploy advanced machine learning solutions, taking models from data and modeling through development and into production. Work with complex datasets and collaborate with business and technical stakeholders in an agile, product-focused environment.
Requirements
Requires a PhD in a relevant quantitative discipline with at least two years of analytical or data science experience, or a master's degree in a relevant technical discipline with at least four years of experience. Candidates should have hands-on expertise in Python, advanced AI/ML, cloud platforms, SQL and Snowflake, MLOps, production software development, and business communication.
Skills
- AI/ML Modeling
- Python
- Machine Learning
- Deep Learning
- Time-Series Forecasting
- Bayesian Statistics
- MLOps
- CI/CD
- Cloud Platforms
- AWS
- GCP
- Azure
- SQL
- Snowflake
- Apache Spark
- Databricks
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Science & Research
Keywords
- Data Science
- Artificial Intelligence
- Machine Learning
- Supervised Learning
- Unsupervised Learning
- Deep Learning
- Time-Series Forecasting
- Bayesian Statistics
- Optimization
- Python
- AWS
- GCP
- Azure
- Databricks
- Apache Spark
- SQL
- Snowflake
- MLOps
- CI/CD
- Model Deployment
- APIs
- Agile
- Git
- Tableau
- Power BI
- Plotly
- Data Visualization
- Relational Databases
- NoSQL Databases