Apply machine learning and analytical skills as a hybrid Data Scientist developing insights from complex datasets. Support data-driven decisions across the organization.

This experienced Data Scientist role focuses on predictive modeling, statistical analysis, and exploratory data analysis. You will develop models, engineer features, tune hyperparameters, and evaluate accuracy, precision, and recall. Collaboration spans engineers, product managers, and business stakeholders.

Key Responsibilities:

- Analyze complex datasets for trends, patterns, and relationships
- Conduct exploratory analysis and formulate data-driven hypotheses
- Develop, deploy, and evaluate predictive machine learning models
- Apply feature engineering, model selection, and hyperparameter tuning




- Communicate findings through statistics and data visualization

Requirements:

- Advanced degree in a related quantitative or technical field
- Proven data science, machine learning, or predictive analytics experience
- Programming proficiency in Python, R, or similar languages
- Understanding of statistics, hypothesis testing, and experimental design
- Experience with TensorFlow, scikit-learn, PyTorch, or comparable frameworks

Use machine learning, statistical analysis, and explicit communication to advance predictive insights in this hybrid Data Scientist role.

📌 Hybrid Machine Learning Data Scientist (Toronto)
🏢 Cognizant
📍 Toronto