Associate Data Scientist

Job description

Area(s) of responsibility Location: Hyderabad / Bangalore / Pune / Noida (Hybrid) Experience: 5–12 Years Employment Type: Full-Time Role Overview We are seeking a highly skilled Data Scientist with strong expertise in Artificial Intelligence (AI), Machine Learning (ML), and MLOps . The ideal candidate will be responsible for building scalable predictive models, driving advanced analytics, and operationalizing ML models in production environments. This role requires a deep understanding of statistical modeling, predictive analytics, and Python-based data ecosystems , with exposure to modern platforms such as Databricks Mosaic AI and Snowflake Cortex being an added advantage. Key Responsibilities • Design, develop, and deploy machine learning and AI models for real-world business problems. • Perform advanced statistical analysis and build predictive models to derive actionable insights. • Develop and implement end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, and deployment. • Build and manage MLOps frameworks for continuous integration, delivery, monitoring, and model governance. • Work closely with data engineering teams to ensure robust and scalable data pipelines. • Conduct exploratory data analysis (EDA) and hypothesis testing to support data-driven decision-making. • Optimize model performance through hyperparameter tuning and advanced techniques. • Deploy and monitor models in production environments ensuring performance, reliability, and scalability. • Collaborate with cross-functional teams including business stakeholders, architects, and product owners. • Stay updated with the latest advancements in AI/ML, GenAI, and data science tools and frameworks. Required Skills & Qualifications • Strong programming expertise in Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch). • Hands-on experience in Machine Learning & AI algorithms (supervised, unsupervised, deep learning). • Expertise in statistical analysis, hypothesis testing, regression, classification, clustering, and forecasting models. • Experience with predictive modeling and advanced analytics techniques. • Solid understanding of MLOps practices including CI/CD pipelines, model versioning, monitoring, and deployment. • Experience working with large-scale datasets and distributed computing frameworks. • Strong knowledge of SQL and data manipulation techniques. • Familiarity with cloud platforms such as AWS, Azure, or GCP. Good to Have • Exposure to Databricks (Mosaic AI, MLflow, Delta Lake). • Experience with Snowflake Cortex / Snowflake ML capabilities. • Understanding of Generative AI / LLM-based applications. • Experience in model explainability, fairness, and governance frameworks. • Knowledge of containerization tools like Docker and orchestration tools like Kubernetes.