Lead Data Scientist

Position: Lead Data Scientist
Experience: 8+ Years
Location: Chennai / Coimbatore / Bangalore / Pune – Hybrid
Required Skills
Classical ML – XGBoost, LightGBM, Regression, Classification
Deep Learning – NLP / Forecasting / Recommendation / Computer Vision
Snowflake – Mandatory, genuine hands-on platform experience
Python & SQL
Azure / Azure ML or similar cloud ML platforms
Databricks / SageMaker / Vertex AI or equivalent
MLOps – MLflow/model registry, CI/CD, automated retraining
Spark / Ray or equivalent distributed computing
GenAI / LLM – RAG, evaluation, monitoring and failure-mode analysis
A/B Testing, Causal Inference, Uplift Modeling
Role Overview
We are looking for a Lead Data Scientist who can set the technical direction for a workstream, make architecture and modeling decisions, and lead a small team of Data Scientists/Engineers.
The candidate should have strong hands-on experience across the complete ML lifecycle and be capable of acting as the senior technical authority for client-facing discussions.
Key Responsibilities
Own the complete model lifecycle from problem framing and feature engineering through training, validation, deployment, monitoring and retraining.
Select and defend appropriate model architectures, including decisions between classical ML and deep learning.
Design and execute rigorous experiments including A/B testing, causal inference and uplift modeling.
Build production-grade feature pipelines and training infrastructure.
Work with distributed computing frameworks such as Spark, Ray or equivalent.
Monitor production models for drift and degradation and determine retraining, redesign or rollback strategies.
Establish technical standards for modeling, code reviews, experiment tracking and model validation.
Mentor and technically guide 2–4 Data Scientists/Engineers.
Act as the primary technical point of contact for clients.
Explain model trade-offs, limitations, assumptions and failure modes to non-technical stakeholders.
Drive GenAI/LLM solutions including retrieval design, evaluation frameworks and production reliability.
Implement MLOps practices including model registries, automated retraining and ML CI/CD.
Must-Have Requirements
8+ years of Data Science experience.
Strong hands-on expertise in classical ML including regression, classification, XGBoost and LightGBM.
Strong deep learning experience with architecture selection and training at scale.
Deep expertise in at least one area: NLP, Forecasting, Recommendation Systems or Computer Vision.
Genuine hands-on Snowflake experience, including architecture and data/training decisions.
Production-scale feature engineering and ML pipelines.
Distributed training / large-scale compute experience using Spark, Ray or equivalent.
Proven ownership of production ML models, including monitoring, drift detection, retraining and rollback.
Strong technical leadership and mentoring experience.
Excellent client-facing communication and ability to defend technical decisions.
Hands-on experience with cloud ML platforms such as Azure ML, Databricks, SageMaker or Vertex AI.
Practical GenAI/LLM experience beyond demo/prototype projects.
Strong MLOps experience with MLflow or similar tools, automated retraining and ML CI/CD.
Consulting/professional services experience with the ability to manage multiple client engagements.
Primary Technical Skills
Python | SQL | Snowflake | XGBoost | LightGBM | Regression | Classification | Deep Learning | NLP | Azure | Azure ML | Databricks | Spark/Ray | MLOps | MLflow | GenAI/LLM | RAG | A/B Testing | Causal Inference | Uplift Modeling
Apply Now
Interested candidates can share their updated CV at Khushboo@Sourcebae.com or WhatsApp it to 8827565832.
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Work arrangement
No