We are looking for an experienced

Senior Data Scientist to deliver enterprise AI and machine learning solutions from exploration to production. The ideal candidate has robust expertise in applied machine learning, statistical modeling, Python, SQL, and cloud-based data science platforms.

What you'll do

- Design, develop, and deploy end-to-end machine learning and data science solutions

- Perform data exploration, feature engineering, model development, validation, and performance evaluation

- Build predictive models for forecasting, classification, regression, recommendation systems, churn prediction, anomaly detection, and marketing optimization

- Conduct experimentation and A/B testing to generate actionable business insights

- Collaborate with data scientists, ML engineers, data engineers, and business stakeholders

- Communicate analytical findings using dashboards, reports, and visualizations

- Support model deployment, monitoring, and production readiness using cloud-based ML platforms

- Contribute to AI and analytics best practices across enterprise initiatives





What you bring

- 8+ years of experience in Data Science and Machine Learning

- Strong expertise in Python, SQL, statistical modeling, and predictive analytics

- Experience with feature engineering, model evaluation, experimentation, and A/B testing

- Hands-on experience with Azure Machine Learning, Databricks, and MLflow

- Experience working with cloud-based AI and analytics platforms

- Knowledge of visualization tools such as Tableau or Power BI

- Strong analytical, communication, and problem-solving skills

- Ability to work independently and collaborate with cross-functional teams

Nice to have

- Experience with recommendation engines, personalization, churn prediction, and anomaly detection

- Knowledge of Azure cloud services and enterprise AI platforms

- Experience deploying production-grade machine learning solutions

- Background in enterprise analytics or AI Centers of Excellence

📌 Senior Data Scientist (Toronto)
🏢 Ju0026M Group
📍 Toronto