Data Modeler

TITLE: Data Modeler

Be Part Of A High-Performing Team:
Join a team at a prominent financial institution known for its dedication to innovation and excellence in the banking industry. The organization values collaboration and operates with a culture that emphasizes integrity, respect, and a commitment to achieving exceptional results. The team works closely with various departments to ensure robust data analytics and cybersecurity measures are in place, driving the company's success in combating insider threats.

What's In Store For You:
- Engagement: W2 only (no C2C/1099)
- Opportunity for professional growth in a cutting-edge field
- Hybrid work model based in Charlotte, North Carolina, providing flexibility and support for work-life balance

How You Will Make An Impact:
- Develop and enhance quantitative models to improve insider risk detection and scoring capabilities
- Collaborate with cybersecurity and data operations teams to centralize and analyze insider risk data
- Transform complex data into actionable insights and risk signals for various stakeholders
- Support governance and regulatory requirements through transparent scoring models and metrics
- Partner with HR, Legal, Compliance, and other teams to drive informed risk management decisions

Do You Have Proven Success in Data Science and Risk Modeling?
- Bachelor's or Master's degree in relevant fields such as Data Science, Statistics, or Computer Science
- Over 5 years of experience in data science or quantitative analysis within financial services or regulated industries
- Proficiency in building statistical or machine learning models, including regression and classification
- Strong skills in Python and/or R, with experience in large-scale data analysis using SQL
- Ability to communicate complex analytical concepts to non-technical audiences
- Experience in supporting Insider Risk, Fraud, AML, Cybersecurity, or Threat Analytics programs
- Familiarity with identity and access data, endpoint telemetry, and related monitoring tools