Responsibilities:

🔹 AI Model Development:

• Develop advanced AI models for financial data analysis, predictive analytics, and forecasting.
• Build and optimize algorithms for risk assessment, fraud detection, and credit scoring.
• Design machine learning systems and improve data-driven decision-making processes.

🔹 Data Engineering:

• Work with large-scale financial datasets, ensuring data quality and scalability.
• Design and implement data pipelines to support AI model training and deployment.
• Collaborate with data engineers to streamline data collection and preprocessing for machine learning projects.

🔹 Performance Optimization:

• Continuously optimize algorithms for accuracy, performance, and efficiency.
• Use techniques like hyperparameter tuning, feature engineering, and model evaluation.

🔹 Collaboration:

• Work closely with data scientists, analysts, and business stakeholders to understand requirements and provide actionable insights.
• Collaborate with development teams to integrate AI solutions into business applications.

Profile:

✅ Degree: Bachelor’s or Master’s degree in Data Science, AI, Computer Science, or a related field.

✅ Experience:

• Proven experience in AI/ML modeling for financial or related sectors.
• Hands-on experience with Python, TensorFlow, PyTorch, or similar ML libraries.
• Strong understanding of financial modeling, risk analysis, and fraud detection.

✅ Technical Skills:

• Deep knowledge of AI/ML algorithms, neural networks, and supervised/unsupervised learning.
• Proficient in Python programming and familiarity with data science frameworks.
• Strong background in mathematical and statistical concepts.