Overview

Data Scientist to develop advanced analytical solutions and machine learning models that drive business value The role focuses on leveraging data applying statistical techniques and building scalable ML models using modern platforms such as Databricks MLflow and Azure ML

Responsibilities

• Develop train and deploy machine learning models using Python Databricks Unity Catalog MLflow and workflows
• Design and implement endtoend ML solutions including data preparation feature engineering model training and evaluation
• Optimize model performance through hyperparameter tuning model selection and validation techniques
• Create and refine features from raw datasets to improve model accuracy and predictive power
• Ensure data quality by processing cleansing and validating datasets
• Conduct exploratory data analysis EDA and data mining to uncover patterns trends and actionable insights
• Develop analytical models to support strategic and operational decisionmaking
• Deploy models using modern ML platforms Databricks Azure ML
• Maintain and enhance existing models ensuring performance and reliability
• Collaborate with engineering teams for scalable production deployment and monitoring
• Work with crossfunctional stakeholders to identify AIMLdriven opportunities
• Maintain clear documentation of models code and analytical processes
• Ensure reproducibility and adherence to data governance standards

Qualifications

• Handson experience in machine learning model development and deployment
• Machine Learning Statistics
• Strong understanding of ML algorithms statistical modeling and data science techniques
• Scikitlearn
• TensorFlow Keras
• Expertise in model evaluation optimization and validation techniques
• MLOps Awareness Positive to Have
• Exposure to ML lifecycle management CICD concepts and model monitoring
• Understanding of model drift observability and performance tracking
• Can share your resume to hidden_email .