Data Scientist-AI/ML
- Toronto, ON, Canada
$49.49 to $59.38 CAD / hour · Contract
Applications open in a new tab.
Job details
- Pay
- $49.49 to $59.38 CAD / hour
- Job type
- Contract
- Apply by
- Posting language
- English
- Posted
Original job description
Can you turn complex data into actionable insights and business intelligence? Apply Now!
Working with one of our top financial clients, this role calls for a Data Scientist-AI/ML to design and deliver end-to-end analytics solutions that combine data science, advanced analytics, and business intelligence. The successful candidate will apply statistical analysis, machine learning, and data-driven experimentation to address complex business challenges, while translating insights into scalable dashboards, reporting solutions, and decision-support tools.
Pay rate range (CAD): $49.49/hr – $59.38/hr
Responsibilities
Privacy Policy
Working with one of our top financial clients, this role calls for a Data Scientist-AI/ML to design and deliver end-to-end analytics solutions that combine data science, advanced analytics, and business intelligence. The successful candidate will apply statistical analysis, machine learning, and data-driven experimentation to address complex business challenges, while translating insights into scalable dashboards, reporting solutions, and decision-support tools.
Pay rate range (CAD): $49.49/hr – $59.38/hr
Responsibilities
- Apply statistical analysis, machine learning, and advanced analytics techniques to identify trends, risks, and optimization opportunities.
- Design and develop analytical models, experimentation frameworks, and data-driven solutions for complex business problems.
- Build and maintain curated datasets, feature layers, and analytical data models supporting modelling and reporting requirements.
- Translate ambiguous business challenges into structured analytical approaches, key performance indicators, and measurable outcomes.
- Create interactive Power BI dashboards, reporting solutions, and executive-ready data stories.
- Partner with stakeholders to define analytical requirements and develop data-driven decision frameworks.
- Validate data quality and support data governance across analytical models and business intelligence outputs.
- Operationalize analytics through automated pipelines, monitoring solutions, and repeatable reporting processes.
- Support risk and control objectives through analytical monitoring and insight generation.
- Continuously improve analytical methodologies, data assets, reporting efficiency, and user adoption.
- Manage multiple priorities and deliver high-quality work within established project timelines.
- Five to seven years of relevant experience in data analytics, data science, business intelligence, or a related field.
- Proficiency in Python, including Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, and PySpark.
- Strong SQL skills, including the ability to write complex queries, stored procedures, and data extraction processes.
- Experience with cloud-based data and artificial intelligence or machine learning platforms such as Azure, AWS, or GCP.
- Experience deploying and managing analytical or machine learning models in production environments.
- Proficiency in Power BI for developing impactful visualizations, dashboards, and reporting solutions.
- Strong organizational skills with the ability to manage multiple deadlines and priorities in a fast-paced environment.
- Ability to collaborate with multiple stakeholders, influence decisions, and achieve alignment across teams.
- Strong risk awareness and the ability to challenge the status quo while proactively managing risks.
- Ability to work effectively in ambiguous situations and simplify complex issues.
- Strong work ethic with the ability to execute efficiently and deliver results with speed.
- Undergraduate or advanced technical degree in mathematics, physics, engineering, finance, computer science, or a related discipline is preferred.
- Proficiency in Tableau.
- Hands-on experience with supervised and unsupervised learning, reinforcement learning, and causal inference.
- Experience building, training, and deploying machine learning models.
- Experience developing model pipelines, feature engineering processes, hyperparameter tuning, and model explainability solutions.
Privacy Policy
More about this job
Responsibilities
Develop end-to-end analytics solutions using statistical analysis, machine learning, and experimentation to address business challenges and identify trends, risks, and optimization opportunities. Build and maintain analytical data assets, dashboards, automated pipelines, and monitoring processes while partnering with stakeholders to support decision-making, data quality, and risk controls.
Requirements
Candidates should have five to seven years of relevant experience, strong Python and SQL skills, proficiency with Power BI, and experience with cloud platforms and production deployment of analytical or machine learning models. A technical degree is preferred, along with strong organizational, collaboration, risk-management, and problem-solving abilities; Tableau and experience with advanced machine learning methods are additional assets.
Skills
- Python
- Pandas
- NumPy
- Scikit-Learn
- TensorFlow
- PyTorch
- PySpark
- SQL
- Cloud Platforms
- Machine Learning Model Deployment
- Power BI
- Statistical Analysis
- Advanced Analytics
- Data Visualization
- Feature Engineering
- Stakeholder Collaboration
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Science & Research
- Finance & Accounting
Keywords
- Data Science
- Machine Learning
- Artificial Intelligence
- Business Intelligence
- Statistical Analysis
- Advanced Analytics
- Data-Driven Experimentation
- Python
- Pandas
- NumPy
- Scikit-Learn
- TensorFlow
- PyTorch
- PySpark
- SQL
- Azure
- AWS
- GCP
- Power BI
- Tableau
- Model Deployment
- Feature Engineering
- Hyperparameter Tuning
- Model Explainability
- Causal Inference
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Data Governance
- Risk Monitoring