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Job Description Senior Data Scientist AI, Predictive Intelligence Agentic Solutions
Location: Bengaluru, India
Work Model: Hybrid Minimum 3 Days per Week in Office
Role Summary
We are looking for a modern, business-facing Senior Data Scientist who can combine predictive analytics, machine learning, Generative AI, agentic architectures, and decision intelligence to solve enterprise problems at scale
This role requires someone who can move seamlessly between business priorities and technical execution designing models, scoring engines, forecasting solutions, LLM-powered workflows, and intelligent systems that create measurable outcomes
The ideal candidate understands that modern data science is no longer only about model accuracy It is about:
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Faster decision-making
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Embedded intelligence in workflows
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Production-ready AI systems
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Commercial value creation
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Cost-efficient model usage
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Trusted and governed AI adoption
This role will support global enterprise functions including:
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Finance
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Customer Experience
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Sales / Commercial
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Operations
Key Responsibilities 1 Predictive Modeling Advanced Analytics
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Design, build, validate, and deploy predictive models that improve business performance
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Develop scoring models, forecasting engines, propensity models, anomaly detection systems, and optimization solutions
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Apply machine learning, statistics, experimentation frameworks, and advanced analytics to improve decisions
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Translate enterprise data into forward-looking business intelligence
Typical Use Cases:
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Churn prediction
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Collections prioritization
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Dispute risk scoring
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Cross-sell / upsell propensity
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Lead prioritization
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Customer lifetime value
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Revenue leakage detection
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Operational SLA risk prediction
2 Generative AI Agentic Solutions
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Design and implement intelligent solutions using LLMs, copilots, and agentic workflows
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Build AI assistants that reason, retrieve knowledge, summarize, orchestrate tasks, and support operational teams
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Develop multi-step AI workflows using APIs, tools, orchestration platforms, and enterprise systems
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Evaluate where autonomous vs human-in-the-loop models are appropriate
Required Understanding:
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Prompt engineering
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RAG architectures
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Tool-use frameworks
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Memory patterns
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Multi-agent orchestration
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Workflow automation with LLMs
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Guardrails and safety layers
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AI observability and quality monitoring
3 AI Economics Model Efficiency
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Understand commercial trade-offs of model usage including token cost, latency, retrieval overhead, orchestration cost, and infrastructure efficiency
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Recommend the right model for the right use case based on quality, speed, and cost
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Optimize prompts, routing logic, and workflows for scalable enterprise deployment
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Evaluate open-source, hosted, and cloud-native model options
4 Business Domain Intelligence
Use data science to solve high-value problems across:
Finance
Customer Experience
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Sentiment analysis
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Case prioritization
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Complaint prediction
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Quality intelligence
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Retention risk scoring
Sales / Commercial
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Opportunity scoring
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Cross-sell targeting
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Pricing intelligence
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Pipeline risk prediction
Operations
5 Visualization Storytelling
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Present insights through dashboards, scorecards, simulations, and executive-ready narratives
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Use Tableau, Power BI, Looker, or Looker Studio
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Convert model outputs into clear business actions
Required Skills Programming Data
Machine Learning
Modern AI Stack
Working knowledge of:
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Vertex AI
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BigQuery
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LLM APIs and model providers
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Embeddings / vector search
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Agent frameworks
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Prompt systems
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Workflow automation tools
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Evaluation frameworks
MLOps / Production Readiness
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Model deployment concepts
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Monitoring drift and performance
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Retraining lifecycle
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Governance and documentation
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CI/CD awareness for data science workflows
Business Communication Skills
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Excellent spoken and written English
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Ability to explain technical concepts to senior business leaders
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Strong consulting mindset solve the real problem, not only the stated request
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Ability to influence through insight and credibility
Qualifications
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Bachelor s or Master s Degree in Data Science, Computer Science, Engineering, Statistics, Mathematics, Economics, or related field
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5+ years of experience in Data Science / Advanced Analytics / Machine Learning roles
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Experience delivering measurable business outcomes
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Enterprise / global environment experience preferred
Preferred Technology Environment
Success Measures
The successful candidate will help deliver:
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Higher model adoption
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Revenue / cost / productivity impact
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Faster time-to-insight
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Strong predictive performance where relevant
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Scalable AI workflows
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Reduced manual effort through automation
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Trusted stakeholder partnerships
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Practical use of next-generation AI
Why Join
This is an opportunity to build enterprise-grade AI solutions from Bengaluru for a global business environment and help shape the next generation of analytics, automation, and intelligent decision systems
Category: Technology
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.