Job Description : Senior Data Scientist - Fraud & Anomaly Detection (Pune, Hybrid)

- Anomaly detection OR Fraud Detection

- Graph neural network

- Python ( Assumed to have a Primary Skill)

Location : Pune (Hybrid)

Experience : 8+ Years

Joining : Immediate to 10 Days

Role Overview :

We are seeking a seasoned Data Scientist with deep expertise in anomaly detection and fraud analytics. The ideal candidate will have hands-on experience with graph-based machine learning models and a strong foundation in Python.

Responsibilities :

- Design and deploy models for anomaly and fraud detection using supervised and unsupervised techniques.

- Implement Graph Neural Networks (GNNs) for relationship-based fraud detection.

- Work with large-scale datasets to extract meaningful insights and patterns.

- Collaborate with engineering and product teams to integrate models into production.

- Optimize model performance and monitor real-time detection systems.

?Required Skills :

- Strong proficiency in Python and libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch.

- Experience with Anomaly Detection techniques (Isolation Forest, One-Class SVM, Autoencoders).

- Proven track record in Fraud Detection across domains (finance, e-commerce, telecom).

- Hands-on with Graph Neural Networks (e.g., GCN, GAT, DeepWalk, Node2Vec).

- Familiarity with Neo4j, NetworkX, or PyG (PyTorch Geometric).

- Excellent problem-solving and communication skills.

Preferred :

- Experience in deploying models in cloud environments (AWS/GCP/Azure).

- Prior work in BFSI or fintech domains.

- Knowledge of MLOps and CI/CD pipelines