Data Scientist

Data Scientist

Experience: 35 Years
Location: PAN India
Role: Data Scientist / ML Engineer
Employment Type: Full-Time

Job Summary

We are looking for a Data Scientist with 3–5 years of experience in Data Science, Predictive Analytics, Prescriptive Analytics, Machine Learning, and MLOps. The candidate will be responsible for developing machine learning models, performing advanced analytics, building scalable solutions using Databricks and Apache Spark, and taking models through the complete lifecycle from development to production.

Key Responsibilities

• Develop and deploy machine learning and predictive analytics models to solve business problems.
• Work on predictive and prescriptive analytics use cases.
• Perform data preparation, exploration, feature engineering, and model development.
• Build scalable data-processing solutions using Databricks and Apache Spark.
• Develop and optimize machine learning pipelines.
• Perform feature engineering and feature selection to improve model performance.
• Evaluate models using appropriate statistical and ML metrics.
• Use MLflow for experiment tracking, model management, and deployment workflows.
• Implement MLOps practices for model lifecycle management and productionization.
• Monitor model performance and identify model/data drift where applicable.
• Work with structured and unstructured datasets to identify meaningful patterns and insights.
• Create data visualizations and communicate analytical findings to technical and business stakeholders.
• Follow data governance, data quality, security, and compliance standards.
• Collaborate with Data Engineers, Business Analysts, ML Engineers, and other stakeholders.
• Document models, experiments, methodologies, and results.

Required Skills

• 3–5 years of experience in Data Science / Machine Learning.
• Strong understanding of Machine Learning and Statistical Modeling.
• Hands-on experience with Predictive Analytics.
• Knowledge of Prescriptive Analytics and optimization-based decision-making.
• Strong experience with Python and relevant data science libraries.
• Hands-on experience with Databricks.
• Good knowledge of Apache Spark / PySpark.
• Strong experience in Feature Engineering.
• Experience with MLflow and ML lifecycle management.
• Understanding of MLOps concepts and practices.
• Experience with Model Evaluation and Validation techniques.
• Good understanding of data governance and data quality.
• Experience creating effective data visualizations and communicating insights.

Good to Have

• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with CI/CD for ML workflows.
• Knowledge of Docker/Kubernetes.
• Experience with model deployment and APIs.
• Knowledge of model monitoring and drift detection.
• Experience with NLP, recommendation systems, forecasting, or optimization.
• Familiarity with Delta Lake and Databricks ML capabilities.