Associate Data Scientist

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.