Key Responsibilities

- Collect, clean, preprocess, and analyze structured and unstructured data.

- Perform exploratory data analysis (EDA) to identify patterns, trends, and business insights.

- Develop, train, test, and deploy machine learning models.

- Apply statistical techniques and predictive modeling to solve business problems.

- Build classification, regression, clustering, and forecasting models.

- Develop data visualizations, dashboards, and reports to communicate findings.

- Work with cross-functional teams, including business analysts, data engineers, and software engineers.

- Optimize model performance and monitor deployed models.

- Perform feature engineering, model validation, and hyperparameter tuning.

- Document methodologies, experiments, and analytical results.

- Ensure data quality, privacy, and compliance with relevant standards.

Required Skills and Qualifications

- Robust programming skills in Python or R.

- Proficiency in SQL and database querying.





- Knowledge of statistics, probability, linear algebra, and hypothesis testing.

- Hands-on experience with machine learning algorithms.

- Experience with libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn.

- Understanding of data preprocessing, feature engineering, and model evaluation.

- Experience with data visualization tools such as Power BI, Tableau, or similar platforms.

- Familiarity with Git and version control.

Preferred Skills

- Experience with TensorFlow, PyTorch, or other deep learning frameworks.

- Knowledge of NLP, computer vision, or generative AI.

- Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.

- Experience with model deployment, APIs, Docker, and ML pipelines.

- Knowledge of MLOps tools and practices.

📌 Data Scientist (Canada)
🏢 Spait Infotech
📍 Canada