Senior Director, Data Scientist

TrimontAtlanta, GA

About The Position

Trimont is seeking an experienced and innovative Senior Director, Lead Data Scientist to join our team. The individual will shape how data is used to inform Trimont leadership, from defining data strategies to implementing advanced tools. Trimont is a specialized global commercial real estate loan services provider and partner for lenders and investors. As the largest master servicer of commercial real estate loans in the United States, Trimont manages securitizations with meticulous oversight and coordination—protecting cash flows, mitigating risk, and ensuring portfolio performance. Trimont is an innovative firm where visionary professionals come to learn, grow, and thrive with colleagues driven by curiosity and collaboration.

Requirements

  • Master’s or Ph.D. in a quantitative discipline.
  • 9+ years of professional data science or advanced analytics experience.
  • Expertise in modern Machine Learning (ML) methods (supervised/unsupervised learning, time series, Natural Language Processing (NLP), etc.).
  • Strong software engineering practices for web tool development and automation.
  • Proven ability to influence business strategy through data insights.
  • Advanced data visualization skills using software, such as Excel, Tableau and/or Power BI
  • GIS mapping skills using Tableau, Surfer, or ArcGIS/ESRI
  • Background in Economics, Finance, and/or Real Estate

Responsibilities

  • Lead end-to-end data science projects: scoping, modeling, deployment, and impact measurement.
  • Oversee end-to-end model lifecycle: data collection and feature engineering, experimentation, validation, monitoring, and retraining in production.
  • Build and maintain robust data pipelines, instrumentation, and monitoring for model performance, data drift, and business KPIs.
  • Partner with stakeholders to set data strategy and identify high-leverage opportunities.
  • Provide technical mentorship and code reviews for other offices and Research staff.
  • Drive best practices in experimental design, feature engineering, and tool monitoring.
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