Data Scientist
ExpiredThe role involves designing and deploying end-to-end machine learning solutions to solve complex business challenges. Key tasks include conducting exploratory data analysis, building predictive models, and collaborating with stakeholders to operationalize AI pipelines.
- Hybrid
- Ontario
- Posted Aug 3, 2026
- Apply by Sep 2, 2026
- 1 position
This job has expired
This position at IMCS Group is no longer accepting applications. The original posting remains below for reference.
Expired Aug 7, 2026
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Original job posting
Job Title: Senior Data Scientist (AI & Machine Learning) Location: Toronto, ON (Hybrid) Duration: 6-12 Months of contract with possible extension Experience: 8-10 Years Role Overview We are seeking an experienced Senior Data Scientist to support Enterprise AI, Machine Learning, and Advanced Analytics initiatives. The ideal candidate will possess strong expertise in applied machine learning, statistical modeling, predictive analytics, and data-driven problem solving. This role requires a highly analytical professional who can independently deliver end-to-end data science solutions while collaborating closely with data scientists, ML engineers, data engineers, and business stakeholders. The successful candidate will be responsible for transforming complex business challenges into scalable AI and analytics solutions, driving projects from data exploration and model development through production readiness and business adoption. Key Responsibilities: Collaborate with business stakeholders to understand problems and translate them into data science and machine learning solutions. Conduct exploratory data analysis and generate actionable insights from large and complex datasets. Design, develop, validate, and deploy machine learning models for business use cases. Perform feature engineering, model selection, hyperparameter tuning, and model evaluation. Build predictive and analytical solutions involving: Classification Regression Forecasting Recommendation Systems Churn Prediction Personalization Marketing Optimization Anomaly Detection Design and analyze experiments, including A/B testing and statistical hypothesis testing. Interpret model results and communicate findings effectively to technical and non-technical stakeholders. Ensure model performance, scalability, and production readiness. Partner with ML Engineers and Data Engineers to operationalize machine learning pipelines. Support best practices in model governance, documentation, and reproducibility. Develop dashboards and visualizations using modern BI tools to communicate trends, predictions, and insights. Required Skills & Qualifications: 8-10 years of experience in Data Science, Machine Learning, Advanced Analytics, or related fields. Strong expertise in: Machine Learning Statistical Modeling Predictive Analytics Data Mining Experimental Design Analytical Problem Solving Advanced proficiency in Python and SQL. Hands-on experience with: Predictive Modeling Forecasting Classification Regression Feature Engineering Model Validation & Evaluation A/B Testing & Experimentation Frameworks Experience building and deploying end-to-end machine learning solutions. Strong understanding of data preparation, model interpretation, and insights generation. Experience working with large-scale structured and unstructured datasets. Excellent communication and stakeholder management skills. Ability to work independently and manage multiple priorities in a fast-paced environment. Preferred Skills: Experience with visualization platforms such as: Tableau Power BI Similar BI/Analytics tools Hands-on experience in cloud-based analytics and machine learning platforms: Azure Machine Learning (Azure ML) Databricks MLflow Azure Data Services Familiarity with MLOps practices and model lifecycle management. Experience in enterprise-scale AI and analytics program delivery. Exposure to healthcare, customer analytics, marketing analytics, or personalization use cases is highly desirable.
What you’ll do
The role involves designing and deploying end-to-end machine learning solutions to solve complex business challenges. Key tasks include conducting exploratory data analysis, building predictive models, and collaborating with stakeholders to operationalize AI pipelines.
Requirements
Candidates need 8-10 years of experience in data science and advanced analytics with high proficiency in Python and SQL. Experience with cloud-based ML platforms like Azure and Databricks is preferred.
Listed skills
- Power BIPreferred
- SQLPreferred
- TableauPreferred
- Machine learningPreferred
- PythonPreferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Machine Learning
- Statistical Modeling
- Predictive Analytics
- Python
- SQL
- Data Mining
- Experimental Design
- A/B Testing
- Feature Engineering
- Model Validation
- Azure Machine Learning
- Databricks
- MLflow
- Tableau
- Power BI
- MLOps
Job areas
- Data & Analytics
- Technology
- Science & Research
- Software
- Engineering
Additional details
- Minimum experience
- 5+ years
- Apply by
- Sep 2, 2026
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available
