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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Peterson Technology Partners Ptp - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $187,200.0 - $228,800.0 - **Contract:** Permanent contract - **Skills:** Mxnet, Agile Methodology, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, IBM ILOG CPLEX Optimization Studio (CPLEX), Data Architecture, Information Engineering, Data Governance, DevOps, Python (Programming Language), Machine Learning, Tensorflow, SQL Databases, Data Streaming, Google Cloud, GaBi Software, Feature Engineering, Pytorch, Large Language Models, Apache Spark, Deep Learning, Model Validation, AI Platforms, Scikit Learn, Information Technology, Xgboost, Machine Learning Operations - **Published:** June 9, 2026 - **Apply:** https://www.dice.com/job-detail/f0ab2fa5-e548-4f3a-bbe6-804dc4b0958b ## About the Role * 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, Google Cloud Platform) 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 skills. Preferred Skills: * Exposure to hospitality, 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 data science. Education: * Master s degree in computer science, statistics, industrial engineering, or related fields required, PhD preferred * 5+ years of experience in data science, operations research, or related area (2+ years for candidates with PhD). ## Description Our client is seeking an Senior Data Scientist to join their team. As a Senior Data Scientist you will design and implement AI, Machine Learning, and Operations Research models that transform business objectives into data-driven solutions. This role advances mission by optimizing decisions, improving operations, and enhancing guest experiences through applied analytics and innovation. The position responsibilities outlined below are not all encompassing. Other duties, responsibilities, and qualifications may be required and/or assigned as necessary., * Translate risk management business requirements into well-defined data science solutions, including incident prioritization and claim severity classification. * Profile, clean, and prepare claims and incident data for analytics, modeling, and scoring. * Develop feature engineering logic using structured and unstructured claims and incident data. * Apply NLP and text-processing techniques to claim and incident narratives to extract useful risk signals. * Develop record-linkage approaches to connect incidents and claims when a clean unique identifier is not available. * Build and validate models that rank incidents by likelihood of becoming claims or requiring Risk Management intervention. * Build and validate claim severity models that classify claims by likely financial impact and high-dollar claim risk. * Generate explain ability outputs, including key risk drivers and business-readable reasons for flagged incidents or claims. * Collaborate with Risk Management, Legal, Data Engineering, BI, Data Governance, and MLOps partners to deliver usable business outputs. * Monitor model performance, drift, scoring quality, and retraining needs. * Document modeling assumptions, feature logic, validation results, limitations, and handoff requirements. * Ensure data science work follows data governance expectations, including appropriate handling of PII and sensitive fields. * Present findings, model results, and recommendations to business and technical stakeholders in a clear, actionable manner., To provide a consistent, fair, and flexible experience for all candidates, we use AI-assisted tools to support parts of the interview process. This includes our proprietary AI platform Pete & Gabi, which includes AI recruiter Rebecca. These AI hiring tools help us: * Conduct recorded video interviews * Transcribe interviews * Summarize candidate responses * Generate job-related insights * Streamline communication and scheduling Please note that: The AI does NOT make hiring decisions; all decisions are made by our human recruiters, hiring managers, or client partners. The AI does not evaluate facial expressions, emotions, or physical traits; it is used only to support fairness, consistency, and efficiency. If you prefer a non-AI interview format, we will gladly provide an alternative. Technical or Case Interviews (Role-Dependent): When applying for certain tech jobs, you may participate in: * A technical interview * A coding challenge * A case study * A client-specific assessment We will always explain what to expect in advance so you can prepare with confidence. Human Review & Selection: Every candidate's profile including interviews, conversations, and assessments is reviewed by experienced recruiters and hiring leaders. 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