Posted 31 May, 2026
559734 | IC | Data Scientist | Bengaluru
ClifyX
Bengaluru,Karnataka,India
Full Time
Reference: 365_594563_26-02536
Description:
About the Role
We are seeking a visionary Data Scientist to drive our AI and advanced analytics initiatives within the Customer & Agency domain. While the role contributes to strategic impact, this is fundamentally a hands-on, build-focused data science role.You will design, experiment, evaluate, and deploy advanced Generative AI, Agentic AI, conversational intelligence, and Intelligent Document Processing (IDP) solutions—especially those supporting conversational claims processing, claims triage, claims document understanding, and customer servicing workflows.You will work closely with Engineering, Product, and Operations to ensure that data science models translate into measurable business value while championing Responsible AI practices across the organization.
Key Responsibilities
• 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.
Qualifications & Skills
Qualification Details
Education Bachelor's or master's in data science, Computer Science, AI, or related quantitative field
Experience 5+ years (Bachelors) or 3+ years post-Masters in AI/Data Science
Programming Expert in Python, SQL, PySpark, scikit-learn, XGBoost/LightGBM, NLP libraries, MLflow for tracking
Use-Case Experience Preferably with Conversational chatbot analytics (intent models, classifier tuning, conversation scoring, document classification or extraction analytics (IDP/OCR evaluation), Retrieval/RAG evaluation for claims, underwriting, or servicing knowledge bases, Churn modeling, clustering/segmentation, recommendation engines, Geolocation/propensity modeling (mandatory experience in one of the following)
Cloud Platforms Hands-on experience with Azure or Google Cloud
MLOps/AIOps Experience in managing ML artifacts, monitoring for drift, data quality checks, CI/CD for model releases and LLM cost optimization is a strong plus
Model Interpretability & Fairness Experience with SHAP/explainers, fairness metrics, bias detection & mitigation in regulated domains
Production Analytics & Monitoring Experience with feature stores,1 batch/streaming scoring, and observability dashboards for model health
Leadership Proven track record managing delivery teams of data scientists and AI engineers
Communication Exceptional ability to communicate across technical and non-technical audiences
Collaboration Strong team player with cross-functional and cross-geography collaboration skills
Problem Solving Demonstrated critical thinking and analytical capabilities
About the Role
We are seeking a visionary Data Scientist to drive our AI and advanced analytics initiatives within the Customer & Agency domain. While the role contributes to strategic impact, this is fundamentally a hands-on, build-focused data science role.You will design, experiment, evaluate, and deploy advanced Generative AI, Agentic AI, conversational intelligence, and Intelligent Document Processing (IDP) solutions—especially those supporting conversational claims processing, claims triage, claims document understanding, and customer servicing workflows.You will work closely with Engineering, Product, and Operations to ensure that data science models translate into measurable business value while championing Responsible AI practices across the organization.
Key Responsibilities
• 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.
Qualifications & Skills
Qualification Details
Education Bachelor's or master's in data science, Computer Science, AI, or related quantitative field
Experience 5+ years (Bachelors) or 3+ years post-Masters in AI/Data Science
Programming Expert in Python, SQL, PySpark, scikit-learn, XGBoost/LightGBM, NLP libraries, MLflow for tracking
Use-Case Experience Preferably with Conversational chatbot analytics (intent models, classifier tuning, conversation scoring, document classification or extraction analytics (IDP/OCR evaluation), Retrieval/RAG evaluation for claims, underwriting, or servicing knowledge bases, Churn modeling, clustering/segmentation, recommendation engines, Geolocation/propensity modeling (mandatory experience in one of the following)
Cloud Platforms Hands-on experience with Azure or Google Cloud
MLOps/AIOps Experience in managing ML artifacts, monitoring for drift, data quality checks, CI/CD for model releases and LLM cost optimization is a strong plus
Model Interpretability & Fairness Experience with SHAP/explainers, fairness metrics, bias detection & mitigation in regulated domains
Production Analytics & Monitoring Experience with feature stores,1 batch/streaming scoring, and observability dashboards for model health
Leadership Proven track record managing delivery teams of data scientists and AI engineers
Communication Exceptional ability to communicate across technical and non-technical audiences
Collaboration Strong team player with cross-functional and cross-geography collaboration skills
Problem Solving Demonstrated critical thinking and analytical capabilities
