Data Scientist - R/Python

<p><p><b>Description :</b></p><p><b><br/></b></p><p><b>Key Responsibilities :</b></p><p><p><b><br/></b></p>- Design, develop, and deploy machine learning and statistical models for predictive and prescriptive analytics.<br/><br/></p><p>- Perform data exploration, feature engineering, and model validation using Python and R.<br/><br/></p><p>- Analyze large datasets to extract patterns, trends, and actionable insights.<br/><br/></p><p>- Develop and maintain data pipelines and automation workflows for analytics solutions.<br/><br/></p><p>- Communicate findings clearly through data visualization and storytelling (R Shiny, matplotlib, seaborn, Power BI, etc.).<br/><br/></p><p>- Collaborate with engineering and product teams to integrate models into production systems.<br/><br/></p><p>- Conduct A/B testing, hypothesis validation, and statistical analysis for business decisions.<br/><br/></p><p>- Stay updated on new technologies, algorithms, and best practices in data science and AI.<br/><br/><b>Required Skills & Qualifications :</b></p><p><p><b><br/></b></p>- 8 - 12 years of hands-on experience as a Data Scientist or in a similar analytical role.<br/><br/></p><p>- Strong expertise in Python and R for data analysis, modeling, and visualization.<br/><br/></p><p>- Proficiency in machine learning frameworks (scikit-learn, TensorFlow, PyTorch, caret, etc.).</p><p><br/></p><p>- Strong understanding of statistical modeling, hypothesis testing, regression, and classification techniques.<br/><br/></p><p>- Experience with SQL and working with large-scale structured and unstructured data.</p><p><br/></p><p>- Familiarity with cloud platforms (AWS, Azure, or GCP) and deployment practices (Docker, MLflow).<br/><br/></p><p>- Excellent analytical, problem-solving, and communication skills.</p><br/></p> (ref:hirist.tech)