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 contemporary 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, including LLM-assisted analysis.
Robust software-engineering practices: testing, code review, and CI/CD.

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