Description

You will build predictive models and statistical solutions to drive credit risk, fraud detection, and portfolio optimization strategies.

This role is on-site.

Responsibilities

• Build and test predictive models for credit risk, fraud, and offer acceptance propensity.
• Develop and validate statistical models and BI reporting tools to enhance origination strategies.
• Create portfolio surveillance solutions for forecasting loan losses and optimizing pricing.
• Implement automation solutions using decision science methodologies and data visualization.
• Lead analyses to provide actionable insights for marketing, sales, and credit decisioning.

Required Skills

• 5 to 8 years of experience in data science or a related role.
• Proficiency in Python, NumPy, Pandas, SciKit-learn, TensorFlow, Keras, and PyTorch.
• Deep understanding of machine learning algorithms, deep learning, and natural language processing.
• Strong Python and PySpark knowledge for data preprocessing and LLM context loading.
• Experience with SQL databases such as MySQL or SQL Server.
• Familiarity with vector databases like Qdrant or Faiss.
• Proven track record of delivering AI projects with measurable business impact.

Preferred Skills

• Master’s or PhD in Computer Science, Data Science, or a related field.

Key Skills

Education

Master’s or PhD in Computer Science