Data Scientist :- Role & Responsibilities Collect, clean, preprocess, and analyze large datasets from diverse data sources. Perform exploratory and statistical analysis to extract meaningful patterns and relationships. Build, train, and evaluate machine learning models for regression, classification, or clustering problems. Implement feature engineering, model selection, and performance evaluation (accuracy, precision, recall, F1 score). Use Python and key libraries (Pandas, NumPy, scikit-learn, Matplotlib, Seaborn, TensorFlow/PyTorch optional). Communicate analytical results and model insights clearly to business and technical teams. Collaborate with data engineers to deploy models into production and improve data pipelines. Stay updated on latest data science tools, frameworks, and trends in AI and ML. Preferred Candidate Profile Experience: 24 years as a Data Scientist or in a machine learningfocused analytics role. Education: Bachelors or Master’s in Data Science, Computer Science, Statistics, Mathematics, or a related field. Technical Skills: Programming: Python (core), SQL (strong proficiency). Libraries: Pandas, NumPy, scikit-learn, Matplotlib, Seaborn (TensorFlow/PyTorch optional). Machine Learning: Regression, classification, clustering, model evaluation metrics. Statistics & Probability: Hypothesis testing, distributions, confidence intervals. Visualization Tools: Tableau, Power BI, or Python-based visualization. (Optional) Big Data & Cloud: Spark, Hadoop, AWS, Azure, GCP. Soft Skills: Strong analytical thinking and data-driven decision-making. Excellent problem-solving and mathematical aptitude. Effective communicator able to translate complex models into business value. Proactive learner with curiosity about new tools and methods.
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