IC | Data Scientist | Bengaluru
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Job Location:
Monthly Salary:
Posted on:
5 hours ago
Vacancies:
1 Vacancy
Job Summary
Total Years: 5 Years
Job Description
Analytical Rigor & Experimentation: Design and run rigorous analytical experiments-including feature engineering hypothesis testing uplift modeling and A/B tests-to improve conversational and claims processing model performance.
Traditional & Applied ML Depth: Build and evaluate predictive and NLP models (e.g. intent classification claims triage document classification) using tree-based methods embeddings and transformer-based techniques.
Generative & Agentic AI: Develop and evaluate LLM/RAG/agentic workflows for claims and customer servicing use cases including prompt evaluation retrieval scoring and reasoning quality checks
Intelligent Document Processing (IDP) Analytics: Develop and evaluate models that validate classify and quality score OCR/IDP outputs for claims documents ensuring accurate entity extraction and workflow routing.
Model Development & Deployment: Build test deliver and maintain robust data science and AI models that solve complex business challenges
Governance & Compliance: Maintain model documentation explainability bias/fairness assessment and align with regulatory expectations for insurance/health.
Responsible AI Leadership: Embed the highest standards of AI ethics and responsible AI in all phases of model development and deployment.
Business Alignment & Impact: Influence and translate strategic business objectives into actionable data science requirements; translate models into measurable outcomes and drive stakeholder adoption and change management.
Health Pillar Support: Drive ideation and delivery of advanced analytics and AI solutions within the health vertical especially on AI-based conversational chatbots.
Innovation & Thought Leadership: Continuously explore and implement best-in-class solutions in Generative and Agentic AI.
Collaboration & Cross Functional Delivery: Partner closely with Engineering Product UX Risk/Compliance Operations and channel teams (web mobile contact center) to plan ship and iterate analytics solutions; co create runbooks enablement materials and ensure smooth handoffs to operations.
Mandatory: Python SQL Azure/Google cloud AI
Job Description
Analytical Rigor & Experimentation: Design and run rigorous analytical experiments-including feature engineering hypothesis testing uplift modeling and A/B tests-to improve conversational and claims processing model performance.
Traditional & Applied ML Depth: Build and evaluate predictive and NLP models (e.g. intent classification claims triage document classification) using tree-based methods embeddings and transformer-based techniques.
Generative & Agentic AI: Develop and evaluate LLM/RAG/agentic workflows for claims and customer servicing use cases including prompt evaluation retrieval scoring and reasoning quality checks
Intelligent Document Processing (IDP) Analytics: Develop and evaluate models that validate classify and quality score OCR/IDP outputs for claims documents ensuring accurate entity extraction and workflow routing.
Model Development & Deployment: Build test deliver and maintain robust data science and AI models that solve complex business challenges
Governance & Compliance: Maintain model documentation explainability bias/fairness assessment and align with regulatory expectations for insurance/health.
Responsible AI Leadership: Embed the highest standards of AI ethics and responsible AI in all phases of model development and deployment.
Business Alignment & Impact: Influence and translate strategic business objectives into actionable data science requirements; translate models into measurable outcomes and drive stakeholder adoption and change management.
Health Pillar Support: Drive ideation and delivery of advanced analytics and AI solutions within the health vertical especially on AI-based conversational chatbots.
Innovation & Thought Leadership: Continuously explore and implement best-in-class solutions in Generative and Agentic AI.
Collaboration & Cross Functional Delivery: Partner closely with Engineering Product UX Risk/Compliance Operations and channel teams (web mobile contact center) to plan ship and iterate analytics solutions; co create runbooks enablement materials and ensure smooth handoffs to operations.
Mandatory: Python SQL Azure/Google cloud AI
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
