Arthur Grand Technologies Inc is looking to solve the problem of debit transaction anomaly detection using AI/ML techniques
Requirements
- Strong proficiency in Python, R, or Scala with experience using data science libraries (e.g., NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow)
- Solid understanding of Data Science with a heavy focus on statistical modeling and Machine Learning, hypothesis testing, regression analysis, and variance modeling
- Experience with anomaly detection techniques — supervised, unsupervised, and hybrid approaches
- Experience in Generative AI based implementations
- Expertise in working with large datasets using SQL, Spark, or similar data-processing frameworks
- Experience in deploying ML models into production environments, MLOps, preferably on AWS
Responsibilities
- Collaborate with stakeholders to understand business objectives and define requirements for anomaly detection
- Develop, optimize, and maintain computational models for debit transaction anomaly detection using AI/ML techniques
- Perform data analysis, generate insights, and identify patterns to support decision-making
- Design and implement statistical models, including standard deviation calculations, variance thresholds, and probabilistic models to enhance anomaly detection accuracy
- Work with existing models to apply backtracking methodologies and improve anomaly reduction strategies
- Leverage machine learning algorithms (e.g., classification, clustering, time-series modeling) to predict, detect, and manage anomalies
- Conduct performance monitoring, fine-tuning, and validation of ML models to ensure accuracy and reliability
Other
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field
- 10+ years of hands-on experience in data science, AI, or ML engineering
- Strong problem-solving, analytical thinking, and communication skills
