Data Scientist developing machine learning models and analytics solutions to improve decisions in the mortgage lifecycle from acquisition to servicing. Collaborating with teams on predictive modeling and automation workflows.
IA
Hybrid Senior Manager, Data Science and Analytics
Posted 5 minutes ago
About the role
- Data Scientist developing predictive models and automation workflows for the mortgage lifecycle. Collaborating with cross-functional teams to enhance operational efficiency and customer outcomes.
Responsibilities
- Develop and maintain machine learning models and statistical tools for use cases such as risk scoring, churn prediction, segmentation, and document classification.
- Collaborate with Product, Engineering, and Analytics teams to identify data-driven opportunities and support automation initiatives.
- Translate business questions into modeling tasks and contribute to the design of experiments and success metrics.
- Assist in building and maintaining data pipelines and model deployment workflows in partnership with data engineering.
- Apply techniques such as supervised learning, clustering, and basic NLP to structured and semi-structured mortgage data.
- Support model monitoring, performance tracking, and documentation to ensure compliance and audit readiness.
- Contribute to internal best practices and participate in peer reviews and knowledge-sharing sessions.
- Stay current with developments in machine learning and analytics relevant to mortgage and financial services.
Requirements
- Minimum education required: Masters or PhD in engineering/math/statistics/economics, or a related field
- Minimum years of experience required: 2 (or 1, post-PhD), ideally in mortgage, fintech, or financial services
- Experience working with structured and semi-structured data; exposure to NLP or document classification is a plus.
- Understanding of model development lifecycle, including training, validation, and deployment.
- Familiarity with data privacy and compliance considerations (e.g., ECOA, CCPA, GDPR) is preferred.
- Strong communication skills and ability to present findings to technical and non-technical audiences.
- Proficiency in Python (e.g., scikit-learn, pandas), SQL, and familiarity with ML frameworks like TensorFlow or PyTorch.
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Senior Manager in Data Science and Analytics leading statistical modeling for mortgage and consumer lending. Collaborating with teams to deliver data - driven insights and improve operational efficiency.
AR
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