1

Financial Data Scientist Jobs (NOW HIRING)

Data Scientist

Washington, DC ยท On-site

$52.88 - $57.69/hr

... finance business data, in addition to traditional data science techniques. This position works to support the developer in the creation, maintenance, and improvement of products, primarily in the ...

You will work across financial and travel spend data, collaborate closely with advisory, forecasting, and engineering partners, and help define how data science shows up in the Clarasight product.

You can also start a savings account or consider financing through our State Farm Federal Credit ... data science, quantitative marketing, operations research, industrial engineering, etc. * Minimum ...

Description Data Scientist American First Finance is seeking a Data Scientist to turn complex data into actionable insights that drive smarter business decisions. In this role, you'll leverage ...

Description Data Scientist American First Finance is seeking a Data Scientist to turn complex data into actionable insights that drive smarter business decisions. In this role, you'll leverage ...

We are a team of tech-savvy cash inventory management experts passionate about helping financial ... Function The Data Scientist will play a critical role in designing, scaling, and operationalizing ...

New

We are a team of tech-savvy cash inventory management experts passionate about helping financial ... Function The Data Scientist will play a critical role in designing, scaling, and operationalizing ...

New

Partner across the company with Product, Engineering, Marketing, Sales, Finance and Data Science teams to shape product strategy using rigorous scientific solutions * Apply statistical, machine ...

Partnering closely with senior Finance leaders and cross-functional stakeholders, you will develop innovative forecasting and predictive modeling solutions that drive performance, support risk ...

Partnering closely with senior Finance leaders and cross-functional stakeholders, you will develop innovative forecasting and predictive modeling solutions that drive performance, support risk ...

Partnering closely with senior Finance leaders and cross-functional stakeholders, you will develop innovative forecasting and predictive modeling solutions that drive performance, support risk ...

Partnering closely with senior Finance leaders and cross-functional stakeholders, you will develop innovative forecasting and predictive modeling solutions that drive performance, support risk ...

You can also start a savings account or consider financing through our State Farm Federal Credit ... data science, quantitative marketing, operations research, industrial engineering, etc. * Minimum ...

We are a team of tech-savvy cash inventory management experts passionate about helping financial ... Function The Data Scientist will play a critical role in designing, scaling, and operationalizing ...

New

We are a team of tech-savvy cash inventory management experts passionate about helping financial ... Function The Data Scientist will play a critical role in designing, scaling, and operationalizing ...

New

We are a team of tech-savvy cash inventory management experts passionate about helping financial ... Function The Data Scientist will play a critical role in designing, scaling, and operationalizing ...

New

We are a team of tech-savvy cash inventory management experts passionate about helping financial ... Function The Data Scientist will play a critical role in designing, scaling, and operationalizing ...

New

next page

Showing results 1-20

Financial Data Scientist information

See salary details

$37.5K

$122.7K

$196.5K

How much do financial data scientist jobs pay per year?

As of Jul 13, 2026, the average yearly pay for financial data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Financial Data Scientist, and why are they important?

To thrive as a Financial Data Scientist, you need strong quantitative skills, proficiency in statistical analysis, and a background in finance or economics, typically supported by a relevant degree. Familiarity with programming languages such as Python or R, experience with machine learning frameworks, and knowledge of financial databases and tools like Bloomberg Terminal are also important. Critical thinking, problem-solving, and effective communication help you translate complex data into actionable insights for stakeholders. These skills are crucial for building accurate financial models, driving data-driven decision-making, and delivering value in dynamic financial environments.

What is the difference between Financial Data Scientist vs Quantitative Analyst?

AspectFinancial Data ScientistQuantitative Analyst
Required CredentialsDegree in Finance, Data Science, or related fields; often certifications like CFA or FRMDegree in Mathematics, Statistics, Finance; CFA or FRM common
Work EnvironmentFinancial institutions, tech firms, investment firms; focus on data modeling and predictive analyticsInvestment banks, hedge funds, asset management; focus on trading strategies and risk modeling
Employer & Industry UsageUsed across finance and tech sectors for data-driven decision makingPrimarily in finance for trading, risk, and portfolio management

Financial Data Scientists analyze large datasets to develop predictive models and insights, often combining finance knowledge with data science skills. Quantitative Analysts focus on developing mathematical models for trading and risk management. While both roles require strong quantitative skills and finance knowledge, Financial Data Scientists tend to work more on data analysis and machine learning, whereas Quantitative Analysts focus on financial modeling and trading strategies.

What does a Financial Data Scientist do?

A Financial Data Scientist analyzes complex financial data using statistical, machine learning, and computational techniques to identify patterns, forecast trends, and support decision-making within financial institutions. They work with large datasets from sources like market data, customer transactions, and economic indicators to develop predictive models and data-driven strategies. Their work helps organizations manage risk, optimize portfolios, detect fraud, and gain a competitive edge in the financial sector.

How does a Financial Data Scientist typically collaborate with other departments within a financial organization?

Financial Data Scientists regularly work alongside cross-functional teams, including risk analysts, portfolio managers, and software engineers. They collaborate to develop predictive models, automate data pipelines, and translate complex data insights into actionable business strategies. Effective communication is key, as they must explain technical findings to stakeholders with varying levels of data literacy. This collaborative environment not only fosters innovation but also offers opportunities to learn from other experts and expand your professional network.
More about Financial Data Scientist jobs
What cities are hiring for Financial Data Scientist jobs? Cities with the most Financial Data Scientist job openings:
What states have the most Financial Data Scientist jobs? States with the most job openings for Financial Data Scientist jobs include:
Infographic showing various Financial Data Scientist job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Data Scientist

Data Scientist

TAD PGS, Inc

Washington, DC โ€ข On-site

$52.88 - $57.69/hr

Contractor

Medical, Retirement

Re-posted 9 days ago


Job description

We have an outstanding Contract position for a Data Scientist to join a leading Company located in the Washington, DC surrounding area.

Pay Rate: $52.88 - $57.69

**US Citizenship is required.**
**Candidate must possess an Active Top Secret/SCI Security Clearance.**

This position develops solutions as part of a combined IT Business Intelligence development and data science team working to integrate the customer's business intelligence reporting capabilities, with a particular focus on IT, cybersecurity, and finance business data, in addition to traditional data science techniques. This position works to support the developer in the creation, maintenance, and improvement of products, primarily in the Power Platform suite, that facilitate comprehensive end-to-end data collection, transform raw data into actionable business insights through statistical analysis, KPI development, PowerBI dashboarding, and proven machine learning methods, and reduce or eliminate manual effort in data processing by automating common processes. The data scientist will propose, implement, and leverage AI and ML solutions to advance the customer's business intelligence capabilities. Data science tasks will include analysis, query, aggregation, visualization, extract/transform/load, complex statements, scripts, stored procedures, triggers, and implementing business intelligence and data warehousing solutions. Mine data using state-of-the-art methods.

Responsibilities:
  • Builds, maintains, and improves dashboards, applications, and automations within the Power Platform (PowerBI, Power Automate, and PowerApps), SharePoint, and InfoPath environments to reduce or eliminate manual effort in data processing by automating common processes.
  • Connects to and leverages application programming interfaces (APIs), system-to-system connections, and manual transfer of data as part of business intelligence extract, transform, and load (ETL).
  • Builds predictive risk models backed by statistical analysis and supports data-driven solutions.
  • Identifies and applies usages of AI and ML to extract key insights from unstructured system documentation for analysis, to automate processes, and to integrate with other applications.
  • Develops and carries out full-service data calls, including the creation of collection applications and forms, data normalization, data cleansing, and visualization.
  • Creates insightful and impactful business intelligence analysis and visualizations to be consumed by senior management, IT system owners, and Division and Field Office leaders.
  • Develops and improves methodologies and tools to assess cybersecurity, financial, and strategic risk at the information system, division, branch, and enterprise level.
  • Researches and recommends business data storage and data integration solutions specific to the IT environment.
  • Develops user guides and documents for business intelligence products.
  • Finds and designs new approaches to handle, analyze, and use large data sets.
  • Solves complex data and storage issues.
  • Analyzes and reports results with actionable recommendations.
  • Connects to and leverages application programming interfaces (APIs), system-to-system connections, and manual transfer of data as part of business intelligence extract, transform, and load (ETL).
  • Incorporates data science tools such as scripting (SQL, R, Python, etc.) into existing and new services to continuously advance available offerings.
  • Identifies, understands, and connects new sources of business intelligence from enterprise holdings that answer key business intelligence questions from leadership.
  • Develops and improves methodologies and tools to assess cybersecurity, financial, and strategic risk at the information system, division, branch, and enterprise level.
  • Works on data collection for regular and ad-hoc data calls for internal and external customers, develops and enhances service requests portals, dashboards and visualizations integrating business data from SharePoint, applications, files, and internal and external data sources, creating and maintaining Power Automations supporting multiple business processes, integration of AI/ML into BI reporting, cleansing, and curation of business intelligence datasets, re-development of a quantitative cybersecurity risk assessment tool, and development of additional quantitative risk assessment tools.

Basic Hiring Criteria:
  • In the absence of years of experience, certifications, or past work may be used to show the level of experience needed to perform at this level.
  • Strong proficiency with the Power Platform, SharePoint, and Infopath tool suite required.
  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc, required.
  • Experience with common data science toolkits, such as R, Weka, NumPy, MATLAB, etc, required.
  • Experience with data science tools and software such as Microsoft Power BI, Anaconda, and Statistical Package for the Social Sciences (SPSS) required.
  • Experience connecting to and extracting/manipulating data from the following systems strongly preferred: Asset Management System (AMS), BigFix, Enterprise Process Automation System (EPAS), Facilities Integration Tool (FIT), Joint Cybersecurity Authorization and Management (JCAM), HR Source/HR Reports, Sentinel, Tenable, Unified Finance Management System (UFMS), Xacta, Microsoft Defender for Enterprise, JIRA, JIRA Service Manager, and CrowdStrike.

Benefits offered to vary by the contract. Depending on your temporary assignment, benefits may include direct deposit, free career counseling services, 401(k), select paid holidays, short-term disability insurance, skills training, employee referral bonus, affordable medical coverage plan, and DailyPay (in some locations). For a full description of benefits available to you, be sure to talk with your recruiter.

Military connected talent encouraged to apply.

VEVRAA Federal Contractor / Request Priority Protected Veteran Referrals / Equal Opportunity Employer / Veterans / Disabled

To read our Candidate Privacy Information Statement, which explains how we will use your information, please visit http://www.tadpgs.com/candidate-privacy/ or https://pdsdefense.com/candidate-privacy/

The Company will consider qualified applicants with arrest and conviction records in accordance with federal, state, and local laws and/or security clearance requirements, including, as applicable:

  • The California Fair Chance Act
  • Los Angeles City Fair Chance Ordinance
  • Los Angeles County Fair Chance Ordinance for Employers
  • San Francisco Fair Chance Ordinance