About the role
Job Description: Role: Data Scientist Duration: 12 months , MISSISSAUGA , ON Remote
Programming & Tools Strong proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch) Working knowledge of statistical analysis and modeling Experience with Jupyter Notebooks, RStudio, and data visualization tools Familiarity with SQL and data querying
Machine Learning & AI Solid understanding of machine learning algorithms (supervised & unsupervised) Hands-on experience with: Regression (linear, logistic), Classification (decision trees, random forests, SVM), Clustering (K-means, hierarchical) Experience with deep learning frameworks (TensorFlow, PyTorch) is a plus
Predictive Modeling Proven experience in predictive modeling and forecasting Ability to build, validate, and deploy predictive models Strong understanding of:
Feature engineering Model evaluation techniques (ROC, precision/recall, cross-validation) Experience working with real-world datasets to derive actionable insights
Statistics & Data Analysis Strong foundation in statistics and probability Hypothesis testing, regression analysis, and statistical modeling Data cleaning, transformation, and exploratory data analysis (EDA)
Data & Deployment (Preferred) Experience with cloud platforms (AWS, Azure, or GCP) Familiarity with Docker/containers is a plus Exposure to MLOps practices (CI/CD for ML models)
Soft Skills Strong analytical and problem-solving skills Ability to translate business problems into data solutions Effective communication and storytelling with data Collaborative mindset with cross-functional teams
Nice-to-Have Experience with big data tools (Spark, Hadoop) Exposure to NLP, computer vision, or time-series forecasting Knowledge of model deployment APIs (Flask, FastAPI)
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About the role
Job Description: Role: Data Scientist Duration: 12 months , MISSISSAUGA , ON Remote
Programming & Tools Strong proficiency in Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch) Working knowledge of statistical analysis and modeling Experience with Jupyter Notebooks, RStudio, and data visualization tools Familiarity with SQL and data querying
Machine Learning & AI Solid understanding of machine learning algorithms (supervised & unsupervised) Hands-on experience with: Regression (linear, logistic), Classification (decision trees, random forests, SVM), Clustering (K-means, hierarchical) Experience with deep learning frameworks (TensorFlow, PyTorch) is a plus
Predictive Modeling Proven experience in predictive modeling and forecasting Ability to build, validate, and deploy predictive models Strong understanding of:
Feature engineering Model evaluation techniques (ROC, precision/recall, cross-validation) Experience working with real-world datasets to derive actionable insights
Statistics & Data Analysis Strong foundation in statistics and probability Hypothesis testing, regression analysis, and statistical modeling Data cleaning, transformation, and exploratory data analysis (EDA)
Data & Deployment (Preferred) Experience with cloud platforms (AWS, Azure, or GCP) Familiarity with Docker/containers is a plus Exposure to MLOps practices (CI/CD for ML models)
Soft Skills Strong analytical and problem-solving skills Ability to translate business problems into data solutions Effective communication and storytelling with data Collaborative mindset with cross-functional teams
Nice-to-Have Experience with big data tools (Spark, Hadoop) Exposure to NLP, computer vision, or time-series forecasting Knowledge of model deployment APIs (Flask, FastAPI)