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Financial Data Scientist Jobs (NOW HIRING)

PangeaTwo

Data Scientist

Homewood, AL · On-site

Partner with Finance, Operations, HR, and Analytics teams to refine models and assumptions ... data science, analytics, or forecasting roles * Strong experience with Python, R, SQL, and data ...

TAD PGS, Inc

Data Scientist

Washington, DC · 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 ...

Point72

Data Scientist

New York, NY · On-site

Requirements * BS, MS or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline. * Programming in Python (or a comparable language) and ...

Aven

Data Scientist

Campbell, CA · On-site

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 ...

Point72

Data Scientist

New York, NY

Requirements * BS, MS or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline. * Programming in Python (or a comparable language) and ...

University of Rochester

Data Scientist

Henrietta, NY · On-site

They are seeking a Data Scientist to design and implement advanced analytics projects, providing ... of financial statements to management reports. • Acts as a focal point for all inquiries ...

Verse

Data Scientist

San Francisco, CA · On-site

$146K - $172K/yr

Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams ... Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster ...

Verse

Data Scientist

San Francisco, CA

$146K - $172K/yr

Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams ... Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster ...

Seneca Holdings

Data Scientist

Yorktown, VA · On-site

... financial benefits back to the members of the Seneca Nation. Position Title: Data Scientist ... Location: Yorktown, Virginia Travel: Occasional CONUS travel required, up to 25% Clearance: Active ...

Lifekind Health

Data Scientist

Scottsdale, AZ · On-site

$80K - $120K/yr

Perform feature engineering using clinical, operational, and financial data * Experiment with ... Master's degree in Data Science, CS, Statistics, Biomedical Informatics, or related field preferred ...

OpenAI

Data Scientist, Strategic Finance

San Francisco, CA · On-site

$290K - $441K/yr

... financial outcomes. * Architect customer segmentation frameworks to unlock tailored growth ... Manage and lead cross-functional data science projects end-to-end. You might thrive in this role if ...

Verse

Data Scientist

San Francisco, CA

$146K - $172K/yr

Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams ... Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster ...

OpenArt

Data Scientist

San Francisco, CA · On-site

$300K - $400K/yr

Data Scientist About OpenArt OpenArt is an AI Storytelling and Visual Creation Platform used by ... Work across product, engineering, data, marketing, and finance - one of the most cross-functional ...

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Financial Data Scientist information

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$37.5K

$122.7K

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How much do financial data scientist jobs pay per year?

As of Jun 11, 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.

Is AI replacing data scientists?

AI is transforming the role of financial data scientists by automating routine tasks and enhancing data analysis capabilities. However, data scientists are still essential for designing models, interpreting results, and making strategic decisions, as AI tools require human expertise for effective implementation and oversight.

Is 40 too late for data science?

A career as a financial data scientist can be pursued at age 40 or older, as the field values skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant technical skills such as programming, statistics, and data analysis tools, making age less of a barrier than skillset and experience.

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.

Can a data scientist work in finance?

A financial data scientist applies data analysis, machine learning, and statistical modeling to financial data to support decision-making, risk management, and investment strategies. They often work with tools like Python, R, and SQL, and may require knowledge of finance concepts and regulations. This role is common in banks, investment firms, and financial technology companies.

What is the salary of data scientist in JP Morgan?

The salary of a Financial Data Scientist at JP Morgan typically ranges from $80,000 to $150,000 annually, depending on experience, location, and skill level. Entry-level roles may start lower, while experienced professionals with advanced skills in machine learning and data analysis can earn higher compensation.

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:
What job categories do people searching Financial Data Scientist jobs look for? The top searched job categories for Financial Data Scientist jobs are:
Financial Data Scientist jobs near you
Infographic showing various Financial Data Scientist job openings in the United States as of June 2026, with employment types broken down into 97% Full Time, and 3% Contract. Highlights an 90% Physical, 3% Hybrid, and 7% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist

Sterling Computers Corporation

North Sioux City, SD • On-site

Full-time

Posted 29 days ago

Job description

Title: Data Scientist

Reports to: Director of Product and Business Development

Location: North Sioux City, SD, Other Sterling Locations

Job Description: Sterling is seeking a highly skilled and motivated Data Scientist to join our growing team. In this role, you will be instrumental in developing and implementing advanced data solutions that enhance our operational and financial reporting capabilities. You will work on internal data science projects, build sophisticated data products, and provide data-driven insights to support our sales teams. Additionally, you will play a key role in our nascent generative AI initiatives, exploring and applying cutting-edge techniques to unlock new possibilities.

Primary Responsibilities

  • Design, develop, and deploy complex data products and models to improve operational efficiency and financial reporting accuracy.
  • Collaborate with cross-functional teams, including operations, finance, and sales, to understand business needs and translate them into data science solutions.
  • Perform in-depth data analysis to identify trends, patterns, and insights that can drive business improvements and inform strategic decisions.
  • Develop and maintain robust data pipelines and integrate various data sources to ensure data quality and accessibility.
  • Support sales teams by providing analytical tools, predictive models, and custom reports that enhance sales performance and customer understanding.
  • Participate in the research, experimentation, and implementation of generative AI models and applications, contributing to the company's innovative efforts.
  • Communicate complex analytical findings and recommendations clearly and effectively to technical and non-technical stakeholders.
  • Stay current with the latest advancements in data science, machine learning, and artificial intelligence.

Qualifications

  • Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline. A Ph.D. is excellent.
  • Strong proficiency in Python is extremely important, including experience with libraries such as pandas, scikit-learn, and PyTorch.
  • Solid understanding and experience with data modeling principles.
  • Proficiency in SQL for data extraction and manipulation.
  • Experience with Databricks.
  • Ability to work alongside data engineers including building and maintaining data pipelines.
  • Proven ability to work effectively alongside data analysts and data engineers, fostering a collaborative environment.
  • Must enjoy working with both technical and non-technical coworkers to understand their problems and collaboratively create innovative data solutions.
  • Demonstrates boundless curiosity and creativity in approaching data challenges.

Preferred Experience:

  • Experience with agentic AI concepts or applications.
  • UI prototyping capabilities, particularly with tools like Streamlit.
  • R programming experience.


Sterling Computers Corporation (“Sterling”) is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to age, race, color, creed, religion, disability, medical condition, economic status or status with regard to public assistance, citizenship status, national or social or ethnic origin, past or present membership in the uniformed services, protected veteran status, sex, pregnancy, marital or civil union or domestic partnership status, family or parental status, sexual orientation, gender expression or identity, family medical history or genetic information, HIV status, political belief, or any other status or characteristic protected by applicable law.