Data Scientist

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

• Strong 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.