Investment Analytics Analyst - AI & Dashboards

National Life Group

Addison (TX)

On-site

USD 47,000 - 69,000

Full time

2 days ago
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Job summary

National Life Group is seeking an Investment Analytics Analyst to support the Office of the CIO across asset allocation, risk management, credit surveillance, and competitive intelligence, leveraging modern data and AI tooling.

The ideal candidate will have a degree in a quantitative field and hands-on experience with Python, SQL, Excel, and BI platforms like Tableau or Power BI, plus familiarity with cloud data platforms and software engineering practices.

Qualifications

  • Degree in Financial Engineering, Data Science, or Computer Science.
  • Experience in financial analysis, analytics, or quantitative development is a plus.
  • Proficiency with Python and SQL is required; Excel and BI tools are essential.

Responsibilities

  • Support the Office of the CIO in providing transparency to investment strategies across the general account.
  • Build and maintain analytical tools, monitors, and dashboards from complex datasets for senior decision-makers.
  • Automate recurring workflows (risk reporting, exposure aggregation, ALM scenario inputs).
  • Assist investment, risk, and operations teams in applying AI to improve turnaround and coverage.
  • Apply software engineering practices (version control, reviews, documentation) to create durable, shareable tools.

Skills

Python
SQL
Excel
AI tooling usage
Cloud data platforms
Code development best practices
Intellectual curiosity
Interpersonal skills

Education

Degree in Financial Engineering, Data Science, or Computer Science

Tools

Tableau
Power BI
Snowflake
Databricks
BigQuery

Job description

National Life Group is seeking an Investment Analytics Analyst to support the Office of the CIO across asset allocation, risk management, credit surveillance, and competitive intelligence, leveraging modern data and AI tooling.

The ideal candidate will have a degree in a quantitative field and hands-on experience with Python, SQL, Excel, and BI platforms like Tableau or Power BI, plus familiarity with cloud data platforms and software engineering practices.

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