Senior Data Scientist

Arintra; Bengaluru; On-site; INR 4,200,000 - 6,600,000; Full time

Job summary

Arintra seeks an senior AI/ML expert to lead data problem formulation and build scalable AI platforms using healthcare and payer data. You will design data strategies, label and curate training data, and mine complex datasets to boost AI accuracy.

Expertise across NLP, traditional ML, and GenAI is essential, with production experience in each. You will architect platforms for training, batch processing, and real-time inference; mentor engineers; and collaborate with data, NLP, and product teams

Qualifications

• 8+ years building and deploying production AI/ML systems.
• Strong experience with complex, domain-specific data and high-cardinality datasets.
• Deep expertise across NLP, Traditional ML, and GenAI, with production experience in each.
• Expert-level PyTorch or TensorFlow with experience in model training at scale.
• Strong hands-on experience with data quality, labeling, and training-data curation.
• Experience with AWS/Azure/GCP and containerized AI workloads using Docker/Kubernetes.

Responsibilities

• Own data problem formulation for AI systems using healthcare, claims, coding, and payer data.
• Design training data strategies, including data extraction, labelling, annotation, and quality improvement.
• Mine large, complex datasets to identify high-value patterns for improving AI/coding accuracy.
• Architect and evolve AI/ML platforms covering training, batch processing, and real-time inference.
• Build multi-modal AI systems using clinical text, structured EHR data, and domain knowledge.
• Evaluate AI tools/platforms and drive build vs. buy decisions.
• Mentor AI engineers across NLP, Traditional ML, and GenAI.
• Collaborate with Data Engineering, GenAI/NLP, and Product teams on data and model strategy.

Skills

NLP

Traditional ML

GenAI

PyTorch

TensorFlow

Data quality

Labeling

Docker

Kubernetes

Cloud platforms

Tools

PyTorch

TensorFlow

Docker

Kubernetes

Job description

Responsibilities:

• Own data problem formulation for AI systems using healthcare, claims, coding, and payer data.
• Design training data strategies, including data extraction, labelling, annotation, and quality improvement.
• Mine large, complex datasets to identify high-value patterns for improving AI/coding accuracy.
• Architect and evolveAI/ML platformscovering training, batch processing, and real-time inference.
• Build multi-modal AI systems using clinical text, structured EHR data, and domain knowledge.
• Evaluate AI tools/platforms and drive build vs. buy decisions.
• Mentor AI engineers across NLP, Traditional ML, and GenAI.
• Collaborate with Data Engineering, GenAI/NLP, and Product teams on data and model strategy.

Requirements:

• 8+ years building and deploying production AI/ML systems.
• Strong experience with complex, domain-specific data and high-cardinality datasets.
• Deep expertise across NLP, Traditional ML, and GenAI, with production experience in each.
• Expert-level PyTorch or TensorFlow with experience in model training at scale.
• Strong hands-on experience with data quality, labelling, and training-data curation.
• Experience withAWS/Azure/GCPand containerized AI workloads usingDocker/Kubernetes.