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.
- Solid 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 [email protected] or WhatsApp it to (phone hidden).

Stay updated with our latest job opportunities and company news by following us on LinkedIn:

Sourcebae on LinkedIn

📌 Lead Data Scientist (Chennai)
🏢 Sourcebae
📍 Chennai