Full-Stack Data Scientist Machine Learning Engineer (MLE)

*7+ years' experience*

Responsibilities
- Design, develop, and validate machine learning and heuristic models, driving measurable improvements in predictive accuracy and business impact.
- Establish and mature the MLOps framework, spanning model registry and versioning, governed development-to-production promotion, automated retraining, and drift and performance monitoring.
- Design and maintain Airflow orchestration for training, inference, and retraining pipelines.
- Own ongoing model operations: monitor model health, diagnose anomalies, and deliver timely remediation.
- Collaborate with data engineering on feature and scoring pipelines and operationalize models through the serving layer.
- Document model methodology, assumptions, and diagnostics to support governance and peer review.

Must-Have
- 7+ years in applied machine learning or data science, with a demonstrated record of deploying models to production environments.
- Advanced proficiency in Python and modern ML libraries (e.g., scikit-learn, XGBoost,



or comparable gradient-boosting frameworks).
- Hands-on MLOps expertise: model registry, development-to-production promotion, monitoring, and reproducible retraining.
- Proficiency in workflow orchestration (Airflow) and cloud services (AWS — S3, IAM, boto3).
- Sound judgment in selecting between statistical, heuristic, and machine learning approaches based on problem context.

Positive-to-Have
- Deep grounding in statistics — hypothesis testing, regression, distributional analysis, time-series methods, and uncertainty quantification.
- Structured problem-solving — translating ambiguous business questions into testable, data-driven hypotheses.
- Experimentation and causal inference — experimental design, backtesting, and retrospective validation.
- Stakeholder communication — articulating model behavior and trade-offs to non-technical audiences.
- Exposure to generative AI and agentic workflows, includin

📌 Full-Stack Data Scientist Machine Learning Engineer (Delhi)
🏢 EY
📍 Delhi