Senior Manager

Position Summary

We are looking for a skilled Data Scientist to contribute to the development and implementation of machine learning models and advanced analytics solutions aimed at enhancing decision-making throughout the entire mortgage lifecycle, from initial acquisition to ongoing servicing. In this practical, hands-on capacity, you will be instrumental in building predictive models, developing customer segmentation tools, and creating automation workflows designed to boost operational efficiency and improve customer outcomes. You will collaborate closely with senior data scientists and cross-functional teams to transform business requirements into well-defined modeling tasks. This role offers opportunities to apply your expertise in natural language processing (NLP), statistical modeling, and experimentation frameworks within a regulated financial services environment. The position reports to a senior leader within the Data Science department.

Job Functions And Responsibilities

• Develop and maintain machine learning models and statistical tools for critical use cases including risk scoring, churn prediction, customer segmentation, and document classification.
• Partner with Product, Engineering, and Analytics teams to identify data-driven opportunities and support the advancement of automation initiatives.
• Translate complex business questions into actionable modeling tasks and contribute to the design of experiments and the definition of success metrics.
• Assist in the construction and upkeep of data pipelines and model deployment workflows in collaboration with data engineering specialists.
• Apply techniques such as supervised learning, clustering, and fundamental NLP to analyze structured and semi-structured mortgage data.
• Support the ongoing monitoring of model performance, tracking key metrics, and maintaining documentation to ensure compliance and audit readiness.
• Contribute to the establishment and refinement of internal best practices, actively participating in peer reviews and knowledge-sharing sessions.
• Stay abreast of the latest developments in machine learning and analytics pertinent to the mortgage and financial services sectors.

Qualifications

• Minimum Education: Master's or PhD degree in Engineering, Mathematics, Statistics, Economics, or a closely related quantitative field.
• Minimum Experience: 2 years of relevant experience, or 1 year post-PhD. Prior experience in the mortgage, fintech, or financial services industry is highly preferred.
• Required Certifications: None specified.
• Specific Skills and Abilities:
  • Demonstrated experience working with structured and semi-structured data. Exposure to Natural Language Processing (NLP) or document classification is considered a significant advantage.
  • Solid understanding of the complete model development lifecycle, encompassing training, validation, and deployment phases.
  • Familiarity with data privacy regulations and compliance considerations, such as ECOA, CCPA, and GDPR, is preferred.
  • Exceptional communication skills with the proven ability to present findings effectively to both technical and non-technical audiences.
• Software or Application Experience:
  • Proficiency in Python, including libraries like scikit-learn and pandas, and strong SQL skills are essential. Familiarity with machine learning frameworks such as TensorFlow or PyTorch is required.
• Mobile Technology Experience: None specified.
• Other Requirements: No other specific requirements beyond those listed above for an ideal candidate.