Asset-Based Finance Data Analytics Associate

KKR; Dallas (TX); On-site; USD 70,000 - 110,000; Full time

Job summary

K-Star Investment Services, a subsidiary of KKR, seeks a Residential Mortgage / Consumer Loan Data Analytics Associate to join its ABF Investment Services Team in Dallas. You will support data management for residential and consumer loans, build end-to-end pipelines, and provide analytics for senior leadership while collaborating with investment teams.

Ideal candidates have 3–5 years in financial services data analytics and strong SQL/Python skills, with a proven ability to automate processes

Qualifications

• Minimum of a Bachelor’s degree.
• 3-5 years of experience in Data Analytics within the Financial Services industry with exposure to residential / consumer data.
• Advanced knowledge of MS Suite, SQL, and Python. Other programming languages are a plus.
• Strong initiative, organization, attention to detail, and ability to learn quickly.
• Excellent written, verbal and interpersonal communication skills.
• Team-oriented with strong integrity and professionalism.
• Experience in process improvement and automation.

Responsibilities

• Support the Asset-Based Finance group with data management related to residential and consumer loans.
• Design and develop automated end-to-end pipelines to ingest, normalize, and standardize data.
• Maintain centralized databases in Snowflake, using SQL to transform or analyze data and create downstream reporting.
• Synthesize multiple data sources to produce meaningful reporting and analytics with actionable insights for Senior Leadership and other stakeholders.
• Serve as primary liaison between business stakeholders and engineering teams, either as the engineer building out the project or assisting our technology team with requirements.

Job description

K-Star Investment Services, a subsidiary of KKR, seeks a Residential Mortgage / Consumer Loan Data Analytics Associate to join its ABF Investment Services Team in Dallas. You will support data management for residential and consumer loans, build end-to-end pipelines, and provide analytics for senior leadership while collaborating with investment teams.

Ideal candidates have 3–5 years in financial services data analytics and strong SQL/Python skills, with a proven ability to automate processes