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Data Scientist
senior · Data Science & Analytics
Bring your expertise to a Home Lending Data and Analytics team that partners with sales leaders to solve complex business problems. You’ll deliver actionable insights that improve strategy, performance, and customer outcomes. You’ll combine strong data skills with business context to drive measurable impact. You’ll work in a fast-paced, matrixed environment with close stakeholder partnership and clear ownership of outcomes. If you enjoy turning data into decisions, this role is for you.
Job summary
As a Quantitative Analytics Senior Associate in Home Lending Data and Analytics supporting Sales, you deliver advanced analytics that informs sales strategy and optimization. You combine data manipulation, quantitative analysis, and business judgment to identify opportunities and recommend actions. You build clear reporting and compelling narratives that help stakeholders make decisions with confidence. You explore opportunities to apply automation and artificial intelligence to improve analytics workflows and business outcomes.
Job responsibilities
- Deliver advanced analytics and data-driven solutions for a wide range of home lending sales business challenges
- Explore, assemble, organize, and analyze data using internal and external data sources and tools
- Perform descriptive, diagnostic, and predictive analyses to uncover trends, patterns, and actionable insights
- Create clear visualizations and narratives that communicate insights and recommendations to business stakeholders
- Identify opportunities to enhance business intelligence and automate reporting to support decision-making
- Build analytical frameworks that support strategic and complex business priorities
Collaborate with business and technology partners to strengthen data foundations and apply artificial intelligence to automate and deliver innovative solutions
Required qualifications, capabilities, and skills
- Bachelor’s or advanced degree in an analytical field (for example, computer science, economics, mathematics, statistics, engineering, or operations research)
- Two years of experience in data analysis or data science
- Proficiency with SQL for data extraction, transformation, and validation
- Proficiency with Python for analysis and automation
- Proficiency with Microsoft Excel for analysis and reporting
- Experience using data visualization tools to communicate insights
- Strong critical thinking skills, including the ability to connect analysis to business strategy and measurable outcomes
- Strong written and verbal communication skills, including data storytelling for business stakeholders
Preferred qualifications, capabilities, and skills
- Experience using cloud platforms for large-scale data processing (for example, Amazon Web Services or Snowflake)
- Experience with Salesforce for lead management and sales workflows
- Experience using GitHub for collaborative analytics and version control
- Strong experience with visualization tools, including products with artificial intelligence and natural-language capabilities
- Experience in financial services, including mortgage business experience