Data Scientist

Responsibilities

• Develop and deploy machine learning models for credit risk scoring, fraud detection, and customer segmentation
• Translate complex business problems into analytical frameworks and measurable outcomes
• Perform exploratory data analysis on structured and unstructured datasets
• Design scalable machine learning pipelines in collaboration with engineering teams
• Lead model validation, explainability, and regulatory compliance processes
• Present insights and model performance results to senior stakeholders

Requirements

• Mandatory exposure to financial services use cases (Credit underwriting, Fraud/AML, EWS, or Collections optimization)
• Proficiency in Python
• Experience with Scikit-learn, TensorFlow, PyTorch, or XGBoost
• Strong SQL and Big Data ecosystem skills (Spark, Hive)
• Experience with cloud platforms (AWS, Azure, or GCP)
• Senior level: 8–10 years of experience; Mid-level: 5–7 years of experience

Preferred Qualifications

• Exposure to Large Language Models (LLMs) and applied AI solutions
• Experience with R or Scala
• Knowledge of Deep Learning, NLP, Time Series modeling, or Graph Analytics
• Previous experience in Banks, NBFCs, or Microfinance organizations

About the Company

AccelOne operates an AI & Data Center of Excellence focused on delivering advanced analytical and machine learning solutions for core financial decision-making.