Compunnel Inc.

Compunnel Inc.

Senior Data Scientist

Chicago, Illinois, USA · Senior · Contract

Sponsorship not specifiedDetected 41 days ago
PythonSQLAWSGCPAzureCloud PlatformsCI/CDDevOpsMachine LearningDeep LearningTensorFlowPyTorchscikit-learnSparkData EngineeringData ScienceNLPLLMsMLOpsStatisticsResearchCommunicationCollaboration

About the role

  • The ideal candidate will have expertise in machine learning, operations research, predictive analytics, and large-scale data processing within cloud-based environments.

Responsibilities

  • Develop advanced feature engineering techniques utilizing claims, incident, and operational datasets.
  • Design and implement record-linkage methodologies to connect related incidents and claims when unique identifiers are unavailable.
  • Develop predictive models that identify incidents likely to become claims or require intervention.
  • Build and validate claim severity models to estimate financial impact and identify high-risk claims.
  • Collaborate with Risk Management, Legal, Data Engineering, Business Intelligence, Data Governance, and MLOps teams to deliver business solutions.
  • Document model assumptions, feature engineering approaches, validation results, and limitations.

Requirements

  • Masters degree in Computer Science, Statistics, Industrial Engineering, Data Science, or a related field.
  • 2+ years of relevant experience may be considered for candidates with a PhD.
  • Experience with insurance claims analytics, risk analysis, and fraud detection.
  • Expertise in operations research methodologies, including Linear Programming (LP), Integer Programming (IP), and Mixed Integer Programming (MIP).
  • Experience using optimization tools such as CPLEX, Gurobi, or similar platforms.
  • Strong experience with feature engineering, model evaluation, model validation, and hyperparameter tuning.
  • Advanced proficiency in Python, SQL, and Spark.
  • Experience working with large-scale datasets and distributed data processing technologies.
  • Experience with streaming data architectures and real-time data processing.
  • Experience working in Agile development environments.

Nice to have

  • Experience supporting hospitality, travel, service industry, or customer operations analytics initiatives.
  • Strong understanding of data architecture principles and MLOps best practices.
  • Proven ability to translate complex analytical findings into measurable business outcomes.
  • Experience with model governance, monitoring, explainability, and lifecycle management.
  • Experience working with cross-functional business and technical teams in enterprise environments.
  • Translate business requirements into scalable data science solutions focused on risk analysis, claims prioritization, fraud detection, and claim severity prediction.
  • Profile, cleanse, and prepare structured and unstructured data for modeling, analytics, and scoring activities.
  • Apply NLP and text analytics techniques to extract insights from claim and incident narratives.

Benefits

  • Develop machine learning solutions using supervised, unsupervised, and deep learning techniques.
  • Support deployment and operationalization of machine learning solutions in cloud environments.

This listing is sourced directly from Compunnel Inc.'s careers page and normalized into a canonical job model.