SSE (Data Scientist, AI /ML)

bout the Role

AI/ML Engineer

Key Responsibilities

• Design, develop, and deploy end-to-end Big Data and Machine Learning solutions at enterprise scale.
• Build and maintain Big Data preprocessing and ETL pipelines ensuring consistency, reproducibility, and data quality.
• Work on advanced analytical use cases such as:
• Churn Modelling
• Risk & Fraud Modelling
• Propensity Modelling (Up-sell/Cross-sell)
• Market Basket Analysis
• Recommender Systems
• Time Series Forecasting
• Anomaly Detection
• Segmentation & Campaign Planning
• Implement and optimize statistical and econometric models including GLMs, Bayesian modelling, clustering, causal inference, hypothesis testing, etc.
• Develop and fine-tune classical ML models using Random Forest, XGBoost, SVM, Bagging/Boosting, kernel methods, etc.
• Collaborate with cross-functional teams to integrate ML solutions into production systems.
• Conduct automated testing, model validation, and performance optimization.
  

Required Skills

AI/ML & Statistical Expertise

• Strong hands-on experience in classical ML algorithms and predictive modelling.
• Deep knowledge of statistical modelling techniques:
• GLMs, clustering, time-series models
• Bayesian modelling, causal modelling, hypothesis testing
• Design of Experiments (DoE)
  

Big Data Engineering

• Strong experience building Big Data pipelines using:
• PySpark / Spark MLlib
• Hive, Hadoop
• Ability to write efficient, scalable data preprocessing and ETL workflows.
  

Programming & Fundamentals

• Expert-level proficiency in Python and SQL.
• Solid understanding of data structures, algorithms, design patterns, object-oriented programming, automated testing, and performance optimization.
  

Cloud & Distributed Systems

• Experience with cloud platforms such as AWS, GCP, or Azure.
• Working knowledge of distributed systems and scalable ML architectures.
  

Deep Learning (Good to Have)

• Working experience with TensorFlow, PyTorch, and deep learning architectures such as:
• RNNs
• LSTMs
• Transformers
• LLM-based models
  

SAS Expertise (Added Advantage)

• Hands-on experience with SAS Suite (E-Miner, Financial/Fraud modules) is a plus.
  

Required Skills

Who Should Apply

• Candidates with a strong mathematical/statistical background.
• Engineers who have productionized ML models and worked on enterprise-scale Big Data pipelines.
• Immediate joiners or those serving notice.