Key Responsibilities

📍Collect, clean, and analyze large and complex datasets to identify patterns, trends, and insights that inform business decisions. 📍Design, develop, and implement machine learning models, algorithms, and statistical techniques to solve real-world business problems. 📍Collaborate with stakeholders to translate business requirements into well-defined analytical solutions. 📍Create and maintain dashboards, reports, and visualizations that make insights easily understandable for non-technical stakeholders. 📍Perform exploratory data analysis (EDA) to generate hypotheses, test assumptions, and guide further analysis. 📍Continuously evaluate model performance and improve accuracy, scalability, and efficiency. 📍Partner with data engineering teams to ensure robust data pipelines and infrastructure for analytics and machine learning. 📍Communicate complex results in a clear and concise manner, tailoring the message for technical and non-technical audiences. 📍Stay updated with the latest advancements in machine learning, AI, and data science to bring innovative techniques to the organization.

Required Skills and Qualifications

📍3–7 years of proven experience as a Data Scientist, preferably in a product-based or fast-paced environment. 📍Strong expertise in Python or R for data analysis, modeling, and scripting. 📍Hands-on experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or similar. 📍Proficiency in SQL and working with relational as well as non-relational databases. 📍Strong statistical knowledge and experience applying hypothesis testing, regression, time-series forecasting, clustering, classification, and other advanced techniques. 📍Experience in building, deploying, and monitoring machine learning models in production environments.

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