[Remote] Data Scientist
Note: The job is a remote job and is open to candidates in USA. The Judge Group is seeking a Data Scientist to design and implement machine learning and natural language processing solutions to support risk and incident analytics. The role involves building predictive models and partnering with cross-functional teams to enhance data-driven decision-making and improve operational outcomes.
Responsibilities
- Translate ambiguous business problems into clearly defined data science solutions aligned with measurable KPIs
- Design, build, and deploy machine learning models for incident prioritization, claim prediction, and severity classification
- Develop feature engineering pipelines using structured and unstructured data sources
- Apply NLP techniques to extract insights from incident and claim narratives
- Implement record linkage methods to connect related datasets without clean unique identifiers
- Build and validate predictive models to assess risk likelihood and financial impact
- Generate explainable outputs, including key drivers and interpretable insights for business users
- Partner with cross-functional teams including Risk, Legal, Engineering, Analytics, and Governance to deliver scalable solutions
- Monitor model performance, data drift, and system reliability; iterate and retrain models as needed
- Document methodologies, assumptions, and validation results to ensure reproducibility and transparency
- Ensure compliance with data governance standards, including proper handling of sensitive data
- Communicate insights and recommendations to technical and non-technical stakeholders
- Mentor junior team members and contribute to a culture of continuous learning and innovation
Skills
- Master's degree in Computer Science, Statistics, Industrial Engineering, or a related technical field, or equivalent practical experience
- 5+ years of experience in data science, machine learning, or operations research (or 2+ years with a PhD)
- Experience building and deploying ML models using Python and SQL
- Experience with feature engineering, model evaluation, and optimization techniques
- Experience working with large-scale data processing frameworks (e.g., Spark)
- PhD in a quantitative field
- Experience with operations research methods (e.g., linear programming, mixed-integer programming) and related tools
- Experience with NLP and text analytics
- Experience working with cloud platforms (e.g., AWS, Azure, or GCP)
- Familiarity with MLOps, CI/CD pipelines, and production model monitoring
- Experience with streaming or real-time data systems
- Strong understanding of data governance and responsible AI practices
- Ability to translate complex analytical results into business impact
- Excellent communication and collaboration skills
Company Overview
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