Straive - Data Scientist - Machine Learning

Description :

Key Responsibilities :

- Work with large datasets to identify patterns, trends, and anomalies that may indicate fraudulent activity

- Utilize data analytics tools and methodologies to conduct in-depth assessments and generate Fraud rules and reports on fraud trends (including first-party and third-party fraud).

- Collaborate with cross-functional teams, including risk management, operations, and compliance, to enhance fraud prevention measures.

- Monitor industry trends, regulatory changes, and best practices to continually enhance fraud prevention strategies.

Technical Skills Needed :

- 3+ years of experience in Python coding, SQL, Machine Learning

- Understanding of Deep Learning/Neural Networks (ANNs)

- Hands on experience with XGBoost, Random Forest, GBM

Experience in end-to-end ML model development :

- Data Preparation

- Feature Engineering

- Model Training & Evaluation

- Model Deployment

Good understanding of :

- Imbalanced data handling

- Model evaluation metrics

- Model explainability

- Exposure to LLMs/RAG concepts

- Cloud exposure is good to have: AWS/GCP/Azure

- Ops tools experience is good to have : Docker/Airflow/Spark/ML Ops

- BFSI domain is good to have, not mandatory