Lead Data analyst

Overview

On Site
Depends on Experience
Contract - W2
Contract - Independent
Contract - 12 Month(s)

Skills

data visualization
aws
gcp
azure

Job Details

Title Lead Data Analyst

Location-Onsite @Mc Lean, VA-Need Locals

Duration Contract

Key Responsibilities

  • Analyze large and complex datasets related to mortgage portfolios, loan performance, and securitization activities.
  • Develop and maintain Python scripts and SQL queries for data extraction, transformation, analysis, and reporting.
  • Support securitization workflows, including data prep, validation, audit checks, waterfall models, and investor reporting.
  • Work closely with business stakeholders, risk, compliance, and finance teams to interpret data and produce actionable insights.
  • Collaborate with cross-functional teams in an Agile environment; manage tasks and stories through Jira.
  • Build dashboards, reports, and automated analytics using Python, SQL, and visualization tools (Power BI/Tableau is a plus).
  • Perform data quality checks, reconcile loan-level data, and help enhance data processes to improve accuracy and efficiency.
  • Document data flows, business rules, and analytical models to ensure transparency and reproducibility.
  • Translate business requirements into analytical solutions and ensure deliverables meet regulatory and investor guidelines.

Required Skills & Qualifications

  • 14 years of experience as a Data Analyst or similar analytical role.
  • Strong proficiency in Python (Pandas, NumPy, data processing & automation).
  • Advanced SQL skills (complex joins, window functions, performance tuning).
  • Solid understanding of Mortgage industry concepts loan origination, servicing, credit risk, delinquency metrics, prepayment, securitization pools, etc.
  • Hands-on experience with Securitization processes (pooling, loan data tapes, waterfall structures, reporting).
  • Experience working in Agile/Scrum methodologies with tools like Jira.
  • Strong analytical and problem-solving skills with the ability to work with large structured/unstructured datasets.
  • Excellent communication skills, able to explain technical concepts to non-technical stakeholders.

Preferred Qualifications

  • Experience with mortgage-backed securities (MBS), ABS reporting, or GSE-related datasets (Fannie Mae, Freddie Mac, Ginnie Mae).
  • Familiarity with data visualization tools such as Power BI, Tableau, or Looker.
  • Understanding of cloud platforms (AWS/Google Cloud Platform/Azure) for data processing is a plus.
  • Knowledge of statistical modeling or machine learning techniques.

Preferred Qualifications

  • Experience with mortgage-backed securities (MBS), ABS reporting, or GSE-related datasets (Fannie Mae, Freddie Mac, Ginnie Mae).
  • Familiarity with data visualization tools such as Power BI, Tableau, or Looker.
  • Understanding of cloud platforms (AWS/Google Cloud Platform/Azure) for data processing is a plus.
  • Knowledge of statistical modeling or machine learning techniques.
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