Assistant Manager - Data Science

About the Role:
Are you a seasoned data science professional passionate about leveraging machine learning to revolutionize the financial sector? Join us as an Assistant Manager – Data Science (ML Lead) to develop cutting-edge models that mitigate risk, predict fraud, and optimize payments for our esteemed financial clients.

Key Responsibilities:

1. Building and Deploying Machine Learning Models:
   • Design, train, and deploy ML models for fraud prediction and merchant risk management.
   • Use supervised learning methods (e.g., Logistic Regression, Decision Trees, XGBoost) for assessing merchant creditworthiness.
   • Implement deep learning models (e.g., Neural Networks, RNNs) for fraud detection and risk assessment in real-time.
2. Advanced Model Development:
   • Explore state-of-the-art ML techniques, including reinforcement learning and graph-based models (e.g., Neo4j, Memgraph).
   • Utilize deep learning architectures like Transformer models (e.g., GPT) to analyze unstructured data.
3. Merchant Underwriting and Creditworthiness Assessment:
   • Develop ML models for underwriting merchants and evaluating their ability to process payments securely.
   • Employ AWS SageMaker, Snowflake, and SQL for data preparation and predictive modeling.
4. Time-Series Forecasting for Loss Prediction:
   • Build advanced time-series models (e.g., ARIMA, SARIMA, Prophet) to forecast losses and optimize risk strategies.
   • Conduct scenario and what-if analysis to minimize financial impacts such as fraud and chargebacks.

Key Skills & Qualifications:

• Strong proficiency in Python (Pandas, NumPy) for data manipulation and model development.
• Expertise in ML frameworks like TensorFlow, PyTorch, and Scikit-learn.
• Experience with deep learning architectures, including Neural Networks, RNNs, and Transformers.
• Familiarity with graph databases (e.g., Neo4j) and advanced fraud detection techniques.
• Proficiency in cloud platforms like AWS SageMaker and Snowflake for data management and deployment.
• Solid SQL skills for data extraction and transformation.

Why Join Us?

• Work on impactful projects in the cutting-edge domains of payments and risk management.
• Be part of a collaborative, innovative team that values continuous learning and professional growth.
• Leverage state-of-the-art tools and frameworks to drive meaningful change in the financial sector.