Lead Data Scientist - Healthcare

Description:

Our Client: Founded in 2020, our client is an industry-leading, first-of-its-kind in India, digital healthcare data platform and exchange, infused with AI/ML capabilities, delivering solutions to stakeholders in all segments of the healthcare sector.

Job Title: Lead Data Scientist

Education: Btech (Degree in Data Science Plus)

Experience: 8 - 10 Years

Location: Bangalore

About the Role: We are developing the next-generation automated health insurance claims processing platform, leveraging AI/ML, deep learning, NLP, OCR, and LLM-powered intelligence. As a Lead Data Scientist, you will drive the design, development, deployment, and optimisation of AI models that power large-scale claims decisioning across multiple regions. This is a high-impact leadership role where you will work independently, set technical direction, mentor a diverse team, and ensure reliable production performance of mission-critical models.

Roles & Responsibilities:

- Design, build, deploy, and monitor ML models for health-claims automation.

- Own full ML pipelines: data ingestion, modelling, deployment, monitoring, retraining.

- Work with NLP, OCR, Transformers, LLMs, and Generative AI.

- Optimise models for accuracy, latency, and scalability.

- Implement MLOps, CI/CD, and production monitoring.

- Collaborate with product and engineering teams; mentor junior members.

Requirements:

- An engineering degree is mandatory.

- 8+ years of experience in data science or machine learning, with 35 years in a leadership role.

- Proven experience building and deploying ML models in production at scale.

- Strong foundation in statistics, machine learning fundamentals, optimisation, and deep learning.

- Expertise in NLP, transformers, LLM fine-tuning, embeddings, computer vision, OCR, time-series modelling, and predictive modelling.

- Advanced proficiency in Python, SQL, ML frameworks, and cloud platforms.

- Demonstrated success leading teams and delivering enterprise-scale AI systems.

- Experience in health-insurance or health-claims processing ecosystems.

- Understanding of regulatory and compliance constraints in healthcare data.

- Knowledge of healthcare data standards such as HL7, FHIR, ICD, CPT, and SNOMED.

- Experience with MLOps tools including MLflow, Kubeflow, Airflow, Docker, and CI/CD pipelines.