Data Scientist

Join a cutting-edge analytics team as a Senior Data Scientist and drive transformative machine learning and NLP solutions for an industry-leading claims and incident mitigation project. Make a real impact by helping risk management teams predict, classify, and proactively address high-risk insurance claims. This is a fully remote opportunity offering exposure to large-scale data challenges, cloud technologies, and cross-functional collaboration-all while advancing your career in applied data science., Design and implement ML and NLP solutions for insurance claims and incident mitigation analytics

• Translate complex risk management business needs into actionable data science strategies
• Profile, clean, and prepare structured and unstructured claims and incident data for modeling
• Engineer advanced features and leverage NLP to extract key risk signals from narrative data
• Apply record linkage techniques to connect disparate data sources without unique identifiers
• Build, validate, and deploy models ranking incidents by claim likelihood and severity
• Classify claims by probable financial impact and assist in fraud detection
• Collaborate closely with Risk Management, Legal, Data Engineering, BI, Data Governance, and MLOps teams
• Monitor model performance, ensure scoring quality, and manage retraining cycles
• Document assumptions, feature logic, validation outcomes, and model limitations
• Present results and actionable insights to both technical and business stakeholders

Master’s degree in computer science, statistics, industrial engineering, or related field (PhD preferred)

• 5+ years in data science, operations research, or related area (2+ with PhD)
• Deep expertise in insurance claims analytics, risk analysis, and fraud detection
• Proficient in operations research modeling (LP, IP, MIP) and optimization tools (CPLEX, Gurobi)
• Advanced skills in machine learning (supervised, unsupervised, deep learning), model evaluation, and feature engineering
• Programming expertise in Python, SQL, Spark; strong command of ML frameworks (Scikit-Learn, XGBoost, Tensorflow, PyTorch, MXNet, LLM)
• Cloud deployment experience (AWS, Azure, GCP) with large, complex datasets
• Hands-on with streaming data architectures, Agile methodologies, DevOps, and CI/CD practices
• Strong communication, documentation, and teamwork abilities

Preferred Skills:

• Background working with data in hospitality, travel, or service industry settings
• Advanced understanding of data architecture and MLOps best practices
• Proven track record translating analytics into measurable business impact
• Demonstrated passion for innovation and continuous learning in data science, Top 3 Must-Haves:* Insurance claims* Risk analysis* Fraud detectionRequired Skills -* Expertise in operations research modeling (LP IP MIP) and tools (CPLEX Gurobi etc)* Expertise in building machine learning models including supervised unsupervised and deep learning methods* Expertise in feature engineering model evaluation and hyperparameter tuning* Expertise in Python SQL and Spark and a broad array of machine learning frameworks (Scikit-Learn XGBoost tensorflow Pytorch MxNet LLM etc)* Experience in developing and deploying solutions in a Cloud environment (AWS Azure GCP) with large datasets* Experience with streaming data architectures* Experience operating in an Agile Methodology environment* Experience with DevOps and CI/CD concepts* Excellent communication and teamwork skillsPREFERRED SKILLS:* Exposure to ho Travel or service industry data and optimization use cases* Strong understanding of data architecture and MLOps best practices* Proven ability to translate complex analytics into business impact* Passion for continuous learning and innovation in applied da

Flexible remote work with collaborative, expert teams

• Exposure to state-of-the-art cloud and AI technologies
• Opportunity to work on high-impact, high-visibility projects
• Professional growth through cross-functional engagement and challenging problem-solving
• Potential contract extension based on performance