Data Scientist (Mid-Level)

USAA

Confirmed live yesterday High trust

Hybrid

Quick summary

Work type: Hybrid
Location: San Antonio, TXPlano, TXPhoenix, AZColorado Springs, COCharlotte, NCTampa, FL
Salary: $114,080–$218,030 / yr
Posted: 4 days ago
Freshness: Confirmed live yesterday
Nearby: 98 roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $158k

This role $166k

$85k most similar roles pay here $232k

This role pays more than 64% of similar roles. Most pay $126,800–$188,765 — the shaded band above. At the midpoint, this role pays about $166k versus about $158k for comparable roles.

Based on 240 similar postings.

Employer

About USAA

USAA (United Services Automobile Association) is a San Antonio-based Fortune 500 financial services company founded in 1922, dedicated to providing insurance, banking, and investment solutions exclusively to U.S. military members, veterans, and their families.

USAA currently has 14 open roles on FindRole.

Listed pay typically runs $143,320–$273,930 across 14 roles with salary data.

Most-posted roles

View all roles at USAA

At a glance

TL;DR · Data Scientist (Mid-Level)

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As a Data Scientist (Mid-Level), you will join the team to translate complex business problems into applied statistical, machine learning, simulation, and optimization solutions. You will gather and manipulate structured and unstructured data to build scalable, automated models that drive actionable insights, revenue generation, and risk reduction. Collaborating with engineering partners and Model Risk Management, you will develop production-ready analytical assets while ensuring stability and compliance within established frameworks. Your daily work involves building a library of reusable algorithms and communicating technical results to non-technical stakeholders. To succeed, you must be proficient in Python or R for modeling, SQL, HQL, and NoSQL for querying databases, and experienced with supervised and unsupervised techniques like regression, decision trees, and clustering. This role focuses on solving financial service challenges through advanced analytics and robust data engineering practices.

What does a Data Scientist earn?

Median $162025 from 276 postings across 61 companies.

See salary data

Skills

Machine Learning Python R SQL HQL NoSQL Simulation Optimization JSON XML Predictive Analytics Data Engineering

What you'll do

Translate business problems into automated statistical, machine learning, simulation, and optimization solutions to drive revenue and reduce risk.
Gather, interpret, and manipulate structured and unstructured data to enable advanced analytical solutions for the business.
Develop and deploy scalable models within the Model Development Control and Model Risk Management frameworks.
Create a library of reusable, production-quality algorithms and supporting code to ensure transparency and high quality.
Compose technical documentation for knowledge persistence, risk management, and technical review audiences.
Communicate complex analytical results and actionable recommendations to non-technical business colleagues.
Collaborate with engineering and IT teams to deploy production-ready assets aligned with customer vision and specifications.
Monitor and control risks associated with business activities in accordance with corporate policy and compliance procedures.

What we're looking for

Bachelor's degree in a quantitative field or 4 years of relevant education and experience.
Advanced degree in a quantitative field and 2 years of experience in predictive analytics or data analysis.
4 years of experience in predictive analytics or data analysis.
2 years of experience training and validating statistical, physical, machine learning, and other advanced analytics models.
2 years of experience using dynamic scripted languages like Python or R for statistical analysis and building AI/ML models.
Experience querying and preprocessing data from structured and unstructured databases using SQL, HQL, or NoSQL.
Experience communicating analytical results to non-technical business partners with a focus on actionable recommendations.
US military experience or Financial Services industry experience (preferred).

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