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.