BENGALURU · FULLTIME
Lead Data Scientist
Arintra
Bengaluru · onsite · Posted 23d ago
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Section · 01
About this role
Requirements:
- Building and deploying production AI/ML systems with demonstrated emphasis on solving the underlying data problem, not just model selection or infrastructure.
- Deep experience working with complex, domain-specific data at scale: extracting signal from noisy real-world datasets, building training data from historical decision records, and handling high-cardinality label spaces.
- Deep expertise across multiple AI domains (NLP, traditional ML, and Gen AI) with production deployments in each.
- Expert-level proficiency in PyTorch or TensorFlow; experience with model training at scale.
- Proven track record on AI/ML projects where data quality, labeling strategy, and training data curation were the primary challenges, not just model architecture or deployment.
- Experience with cloud-native AI architectures on AWS, Azure, or GCP; containerized deployments (Docker, Kubernetes) for AI workloads.
- Preferred Experience building self-improving AI systems: active learning pipelines, feedback loop architectures that connect outcome signals back to model updates, or reinforcement learning from human feedback (RLHF) / outcome-based reward signals.
- Data mining experience at scale across high-cardinality feature spaces, finding rare but high-value patterns across large taxonomy or code spaces.
- Hands-on experience with domain-specific AI systems that learn from historical decisions, e. g., autonomous decision engines, recommendation systems, or classification pipelines that adapt from labeled outcomes over time.
- Experience with MLOps tooling: CI/CD for ML, model versioning, monitoring, and deployment governance.
- Experience in healthcare technology, medical AI, or regulated industries, including HIPAA-compliant system design and audit trail requirements.
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Section · 02
Skills
Section · Company
About Arintra
Arintra
11-50
employees
2020
6 years old
Austin
US
About
US hospitals and clinics are losing $125B every year due to delayed and inaccurate medical coding. Arintra is solving this problem by automating medical coding using AI and clinical NLP. Arintra converts a patient chart instantly into insurance claims with 96% accurate medical codes and zero human intervention.
Arintra solution is specifically tailored to cater to the varying requirements of ambulatory and outpatient specialties, emergency department services, and inpatient settings, ensuring comprehensive coverage across all healthcare domains.
Arintra’s software leverages proprietary artificial intelligence and natural language processing algorithms to process patient charts directly from the EHR to create a direct-to-billing claim. Arintra autonomously goes through every stage of the claim submission process and ensures a clean claim for optimal reimbursements without any human intervention. Arintra is integrated with all the top EHRs to ensure effortless implementation without any change in the workflow.
Arintra’s medical coding software offers two powerful modes for medical coding: autonomous coding mode and assisted coding mode. In autonomous coding mode, direct-to-billing claims are generated autonomously with high accuracy, streamlining the billing process for healthcare provider organizations. Whereas, assisted coding mode allows medical coders to meticulously review and optimize charges before submission, leading to increased efficiency and precision in the coding process. With Arintra, healthcare provider organizations can rely on precise direct-to-billing claims that include essential codes like E/M levels, CPT, ICD-10, HCC, HCPCS with appropriate modifiers and units.
Arintra’s coding solution provides extensive coverage and flexibility, catering to various coding domains such as professional coding, professional-fee coding, facility coding, and inpatient coding.
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Culture
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Career growth
2.0
Work-life
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