Data Analytics Associate – Asset-Based Finance (Residential)

Stage

Dallas (TX)

On-site

USD 85,000 - 120,000

Full time

14 days+

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Job summary

KKR's K-Star Investment Services seeks a Residential Mortgage / Consumer Loan Data Analytics Associate to join its ABF Investment Services Team in Dallas. The role supports data analysis and management for its $30bn portfolio, working closely with the investment team and deal team.

The ideal candidate has 3–5 years' experience in data analytics within financial services, with exposure to residential mortgage or consumer data, and strong SQL, Python, and MS Office skills.

Qualifications

  • Bachelor’s degree required.
  • 3–5 years of data analytics experience in financial services with residential/consumer data.
  • Advanced knowledge of MS Office, SQL, and Python; other languages a plus.
  • Strong initiative, highly organized, detail-oriented, and able to learn quickly.
  • Proven track record of meeting deadlines in a fast-paced environment.
  • Excellent written and verbal communication; team-oriented with integrity.

Responsibilities

  • Support Asset-Based Finance data management for residential and consumer loans.
  • Design and develop automated end-to-end data pipelines.
  • Maintain centralized Snowflake databases and create reporting.
  • Synthesize data sources for reporting and actionable insights for senior leadership.
  • Serve as liaison between business stakeholders and engineering teams.

Skills

SQL
Python
Data analytics
MS Office
Communication
Attention to detail

Education

Bachelor's degree

Tools

Snowflake

Job description

KKR's K-Star Investment Services seeks a Residential Mortgage / Consumer Loan Data Analytics Associate to join its ABF Investment Services Team in Dallas. The role supports data analysis and management for its $30bn portfolio, working closely with the investment team and deal team.

The ideal candidate has 3–5 years' experience in data analytics within financial services, with exposure to residential mortgage or consumer data, and strong SQL, Python, and MS Office skills.

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