Senior Data Scientist

Job Title: Senior Data Scientist – AI, Machine Learning, NLP & Risk Analytics

• Location: Chicago, IL (Hybrid) – Local Candidates Preferred
• Employment Type: Full-Time / Contract (Based on Client Requirements)
• Work Authorization: USC, GC, and H1B Candidates Eligible
• Experience Required: 14+ Years

About the Opportunity

We are hiring on behalf of our client for an experienced Senior Data Scientist with deep expertise in Artificial Intelligence, Machine Learning, Natural Language Processing (NLP), Risk Analytics, and Operations Research. This role requires a seasoned professional capable of developing advanced predictive models, optimization solutions, and AI-driven analytics platforms to support large-scale business operations.

The ideal candidate will possess extensive experience in insurance risk analytics, claims modeling, fraud detection, incident prediction, and advanced optimization techniques while leveraging modern cloud data platforms and AI technologies.

Key Responsibilities

AI, Machine Learning & Advanced Analytics

• Design, develop, and deploy machine learning and predictive analytics solutions.
• Build scalable AI models for risk assessment, incident prediction, and business intelligence.
• Develop explainable AI solutions using techniques such as SHAP, LIME, and related frameworks.
• Collaborate with business stakeholders to translate complex business problems into data science solutions.
• Evaluate and improve model performance, reliability, and governance.

Claims & Risk Analytics

Develop and maintain:

• Claims Analytics models
• Insurance Risk Modeling frameworks
• Fraud Detection and Fraud Analytics solutions
• Severity Prediction Models
• Incident Prediction Models
• Analyze structured and unstructured datasets to identify emerging risks and trends.
• Support underwriting, claims operations, and risk management initiatives through advanced analytics.

Natural Language Processing (NLP) & LLM Applications

• Design and implement NLP pipelines for large-scale text processing.
• Develop solutions involving:
• Text Classification
• Claims Narrative Analysis
• Incident Report Analysis
• Information Extraction
• Semantic Search
• LLM-based Applications
• Fine-tune and deploy NLP models for business-critical use cases.

Operations Research & Optimization

Develop optimization solutions utilizing:

• Linear Programming (LP)
• Integer Programming (IP)
• Mixed Integer Programming (MIP)
• CPLEX
• Gurobi

Responsibilities include:

• Resource allocation optimization
• Scheduling optimization
• Capacity planning
• Network and operational efficiency modeling
• Decision-support systems development

Data Architecture & Governance

• Design scalable data architectures using modern cloud platforms.
• Build and optimize data pipelines using Databricks and Snowflake.
• Establish and maintain data governance standards.
• Ensure proper handling and protection of PII and sensitive business data.
• Collaborate with engineering teams to implement enterprise-grade data solutions.

Industry Analytics

Apply advanced analytics methodologies within:

• Hospitality Industry Analytics
• Travel Industry Analytics
• Insurance Analytics

Required Skills & Qualifications

Mandatory Experience

• 14+ years of experience in Data Science, Machine Learning, AI, or Advanced Analytics.
• Strong experience in:
• Claims Analytics
• Insurance Risk Modeling
• Fraud Analytics
• Incident Prediction
• Severity Modeling
• Explainable AI (SHAP, LIME, etc.)
• Hospitality Analytics
• Travel Industry Analytics
• Data Governance
• PII Handling
• Data Architecture

Technical Expertise

• Machine Learning & Statistical Modeling
• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Databricks
• Snowflake
• Python
• SQL
• Spark
• Cloud-based Analytics Platforms

Optimization & Operations Research

Hands-on experience with:

• Linear Programming (LP)
• Integer Programming (IP)
• Mixed Integer Programming (MIP)
• CPLEX
• Gurobi

Preferred Qualifications

• Experience working in insurance, travel, hospitality, or risk management domains.
• Experience deploying AI models in production environments.
• Strong stakeholder communication and leadership skills.
• Experience mentoring junior data scientists and analytics teams.

Nice to Have

• MLOps and Model Governance experience.
• Generative AI and Agentic AI implementation experience.
• Experience with knowledge graphs and advanced recommendation systems.
• Experience with cloud platforms such as AWS, Azure, or GCP.

How to Apply

Qualified candidates meeting the above requirements are encouraged to apply with their updated resume, including project details highlighting experience in AI, Machine Learning, NLP, Risk Analytics, Claims Analytics, Insurance Modeling, Fraud Detection, and Optimization Solutions.

Note: Local candidates near Chicago, IL will be given preference for this hybrid opportunity.