Senior Associate Data Scientist, Applied AI

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Plano, TX
Salary: $135,600–$154,800 / yr
Employment: Full-time
Posted: 2 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $184k

This role $145k

$125k most similar roles pay here $234k

This role pays less than 78% of similar roles. Most pay $152,500–$214,600 — the shaded band above. At the midpoint, this role pays about $145k versus about $184k for comparable roles.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 1756 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 961 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Associate Data Scientist, Applied AI

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Senior Associate, Data Scientist - Applied AI (Financial Services) joins a team focused on delivering Generative AI solutions within the financial services sector. Working alongside cross-functional teams of data scientists, machine learning engineers, and product managers, the individual will build Multi-Agent systems and advanced RAG pipelines using vast amounts of numeric and textual data. The role involves developing models through all phases of production, including context engineering, fine-tuning, evaluation, validation, and deployment. Key technologies include Python, PyTorch, LangChain, AWS, Spark, and Vector Databases. Candidates must possess expertise in deep learning, NLP, information retrieval, and statistical modeling techniques such as clustering, classification, sentiment analysis, and time series. The position requires a technical proficiency with open-source tools and cloud platforms to solve complex problems involving large-scale data processing for financial products.

What does a Data Scientist earn?

Median $162000 from 295 postings across 61 companies.

See salary data

Skills

Python PyTorch LangChain AWS Spark Vector Databases Generative AI RAG SQL Scala R Deep Learning NLP Machine Learning Time Series Sentiment Analysis Clustering Classification

What you'll do

Deliver Generative AI solutions in collaboration with cross-functional teams of data scientists and product managers.
Build Multi-Agent systems and advanced RAG pipelines using Python, PyTorch, LangChain, and Vector Databases.
Develop Generative AI models through all phases including context engineering, fine-tuning, evaluation, and deployment.
Process and analyze vast volumes of numeric and textual data across large-scale datasets.
Translate complex technical work into tangible business goals for non-technical stakeholders.
Research and evaluate emerging technologies to implement state-of-the-art methods in production.
Build and validate machine learning models using techniques like clustering, classification, and sentiment analysis.

What we're looking for

A Bachelor's degree in a quantitative field plus 2 years of experience performing data analytics or a Master's degree in a quantitative field or an MBA with a quantitative concentration.
Experience building models, validating them, and backtesting them using techniques like clustering, classification, sentiment analysis, time series, and deep learning.
Proficiency in developing data science solutions using open-source tools and cloud computing platforms.
Master’s Degree in a STEM field or a PhD in a STEM field (preferred).
At least 2 years of experience with Python, Scala, or R (preferred).
At least 2 years of experience with machine learning (preferred).
At least 2 years of experience with SQL (preferred).
At least 1 year of experience in AI, Information Retrieval, Deep Learning, or NLP (preferred).

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