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The Data Scientist position analyzes new/existing business challenges in order to design and implement innovative AI solutions. These solutions enable our colleagues and clients to fully embrace the advantages of AI and AI-driven automation. These solutions will vary from complete custom-builds to service specific AI components.  We’re looking for dedicated people who are passionate about data science, statistics and operational efficiency.

 

Key Responsibilities

AI Development & Data Science

  • Design, develop and maintain AI/ML solutions for various business units.
  • Drive end-to-end AI/ML development including data preparation, model development/training, testing and performance monitoring.
  • Integrate models into workflows to support Operational goals.
  • Ensure solutions abide by stated organizational policies including data security and privacy.
  • Monitor model performance and continuously improve accuracy and reliability.

Collaboration & Strategy

  • Work closely with operations, client services and IT teams to define automation needs and business requirements.
  • Translate operational challenges into analytical frameworks and AI solutions.
  • Present complex insights in clear, actionable language for management, Operations and IT staff.
  • Support automation initiatives that reduce manual processing and improve efficiency.

Required Skills & Qualifications

  • Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Actuarial Science, or related field.
  • 5+ years professional experience with AI/ML model development and maintenance.
  • Proficiency in SQL and Python (pandas, scikit-learn, NumPy, Pillow).
  • Proficiency with inference engines (Ollama, vLLM)
  • Proficiency with Ubuntu/Linux platforms
  • Proficiency with Docker
  • Proficiency with NLP frameworks (BERT, RoBERTa)
  • Proficiency with PDF Parsing and Extraction tools (Tesseract OCR, PDF Plumber, VLM models)
  • Strong data analysis skills
  • Excellent communication skills, with ability to explain technical findings to both technical and non-technical audiences.

Preferred Qualifications

  • Experience in the insurance industry, claims data structures and/or claims management systems.
  • Knowledge of big data tools (Spark, Hadoop) and cloud platforms (AWS, Azure).
  • Experience with MLOps practices for deploying and monitoring predictive models.