Description

Lead the development and deployment of AI/ML solutions for debit transaction anomaly detection.

This role is on-site.

Responsibilities

• Develop, optimize, and maintain computational models for anomaly detection using statistical and ML techniques.
• Design probabilistic models, variance thresholds, and time-series algorithms to enhance detection accuracy.
• Integrate ML models into production systems in collaboration with engineering and business teams.
• Conduct performance monitoring, fine-tuning, and validation of models to ensure reliability.
• Implement Generative AI solutions and deploy models using MLOps practices.

Required Skills

• 10+ years of hands-on experience in data science, AI, or ML engineering.
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or Mathematics.
• Strong proficiency in Python, R, or Scala with libraries like Pandas, Scikit-learn, PyTorch, or TensorFlow.
• Solid understanding of statistical modeling, hypothesis testing, and regression analysis.
• Experience with supervised, unsupervised, and hybrid anomaly detection techniques.
• Expertise in working with large datasets using SQL or Spark.
• Experience deploying ML models into production environments, preferably on AWS.

Key Skills

Education

Bachelor's or Master's degrees