IN_Senior Associate_Data Scientist _Data and Analytics

Job Description & Summary: A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.

Responsibilities:

About the Role: We are looking for a highly skilled Data Scientist who can work across the entire data science lifecycle from feature engineering and model development to deployment and monitoring using modern ML platforms. The ideal candidate will have hands-on experience with Azure Machine Learning, Databricks, and MLflow, and will be comfortable building scalable solutions for real-world business problems. What will you do: Data Preparation & Feature Engineering Collect, clean, and preprocess structured and unstructured data from multiple sources. Perform feature selection, transformation, and creation for optimal model performance. Model Development Design, train, and validate predictive and prescriptive models using advanced statistical and machine learning techniques. Experiment with algorithms for classification, regression, clustering, and NLP. Model Deployment & Monitoring Deploy models into production using MLflow and Azure ML pipelines. Implement model versioning, reproducibility, and automated retraining strategies. End-to-End ML Lifecycle Management Manage experiments, track metrics, and maintain model registry in MLflow. Ensure compliance with MLOps best practices for scalability and reliability. Collaboration & Communication Work closely with data engineers, business analysts, and stakeholders to translate business requirements into data-driven solutions. Present insights and recommendations through dashboards and reports.

Mandatory skill sets:

Must have knowledge, skills and experiences Technical Expertise Strong proficiency in Python (pandas, scikit-learn, PySpark) and SQL. Experience with Azure Machine Learning, Databricks, and MLflow. Solid understanding of MLOps principles and CI/CD for ML models.

Data Science & ML Hands-on experience in feature engineering, model selection, hyperparameter tuning. Familiarity with deep learning frameworks (TensorFlow, PyTorch) is a plus. Cloud & Big Data Knowledge of Azure services like Azure Data Lake, Azure Fabric, and Azure Functions. Experience working with large-scale data on distributed systems. Soft Skills Strong problem-solving and analytical skills. Excellent communication and stakeholder management abilities.

Preferred skill sets:

Good to have knowledge, skills and experiences Familiarity with data lake architectures and delta lake concepts Familiarity with Azure ML/Databricks ML

Years of experience required: 5-8 years

Education qualification:

o BE, B.Tech, ME, M,Tech, MBA, MCA (60% above)