Senior Data Scientist

As a Senior Data Scientist with 8+ years of experience, your role will involve being highly hands-on and experienced in building, deploying, and optimizing advanced analytics and machine learning solutions. You must have strong expertise in Python, R, and SQL, and the ability to work on end-to-end data science workflows from data exploration and feature engineering to model deployment and performance monitoring. Understanding of Databricks and Azure Data Factory (ADF) is a plus. Key Responsibilities: - Design, develop, and deploy machine learning and statistical models - Perform advanced data analysis and exploratory data analysis (EDA) - Develop scalable ML pipelines using Python / R - Write optimized SQL queries for data extraction and transformation - Perform feature engineering and model validation - Work closely with Data Engineering teams for data preparation and pipeline integration - Communicate insights and model outcomes to business stakeholders - Monitor model performance and implement improvements - Ensure data quality, governance, and compliance standards Qualifications Required: - 8+ years of experience in Data Science / Advanced Analytics - Strong hands-on expertise in Python (NumPy, Pandas, Scikit-learn, etc.) - Strong proficiency in R - Advanced SQL skills - Experience in building and deploying ML models in production - Strong understanding of statistics, probability, and ML algorithms - Experience handling structured and unstructured datasets Additional Details: The ideal candidate should also have working knowledge of Databricks, understanding of Azure Data Factory (ADF), experience with ML lifecycle tools (MLflow, SageMaker, etc.), exposure to cloud platforms (Azure / AWS / GCP), and experience with visualization tools (Power BI / Tableau). As a Senior Data Scientist with 8+ years of experience, your role will involve being highly hands-on and experienced in building, deploying, and optimizing advanced analytics and machine learning solutions. You must have strong expertise in Python, R, and SQL, and the ability to work on end-to-end data science workflows from data exploration and feature engineering to model deployment and performance monitoring. Understanding of Databricks and Azure Data Factory (ADF) is a plus. Key Responsibilities: - Design, develop, and deploy machine learning and statistical models - Perform advanced data analysis and exploratory data analysis (EDA) - Develop scalable ML pipelines using Python / R - Write optimized SQL queries for data extraction and transformation - Perform feature engineering and model validation - Work closely with Data Engineering teams for data preparation and pipeline integration - Communicate insights and model outcomes to business stakeholders - Monitor model performance and implement improvements - Ensure data quality, governance, and compliance standards Qualifications Required: - 8+ years of experience in Data Science / Advanced Analytics - Strong hands-on expertise in Python (NumPy, Pandas, Scikit-learn, etc.) - Strong proficiency in R - Advanced SQL skills - Experience in building and deploying ML models in production - Strong understanding of statistics, probability, and ML algorithms - Experience handling structured and unstructured datasets Additional Details: The ideal candidate should also have working knowledge of Databricks, understanding of Azure Data Factory (ADF), experience with ML lifecycle tools (MLflow, SageMaker, etc.), exposure to cloud platforms (Azure / AWS / GCP), and experience with visualization tools (Power BI / Tableau).