Overview
Lead Arkose’s ML research and team as a builder-manager, setting the technical direction for how machine learning is applied to fraud detection and risk-scoring products.
What you'll do
- Define and drive the Data Science and Machine Learning roadmap by aligning research with product priorities.
- Lead development and delivery of ML models for real-time fraud and risk decisioning.
- Establish MLOps practices including governance, experimentation, and end-to-end lifecycle management.
- Own production model performance, including precision/recall tradeoffs, drift monitoring, and retraining cadence.
- Drive applied research in graph machine learning, behavioral analytics, and intelligent fraud detection systems.
- Manage, coach, and grow a team of ML researchers, including hiring and performance management.
What you'll need
- 6+ years building and deploying ML models in production.
- 2+ years directly managing ML engineers or data scientists.
- Track record of shipping ML systems that moved a real business metric (ideally in fraud/trust & safety/cybersecurity or an adversarial, imbalanced-data domain).
- Strong technical depth to evaluate classification, anomaly detection, graph-based methods, and sequence models.
- Experience across the ML lifecycle: pipelines, feature engineering, training, evaluation, deployment, and monitoring.
- People-management experience including hiring, coaching, and developing individual contributors.
- Excellent cross-functional communication to translate ML trade-offs for non-technical stakeholders.
Details
- Location: Pune, India.
- Work mode: Hybrid.
- Employment type: Director (no explicit employment type stated in source).
Read the full description and apply on the company’s own careers page.
