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Data Science Bank Jobs (NOW HIRING)

Triumph

Director of Data Science

Dallas, TX · On-site

They are looking for a Director of Data Science to design and operationalize quantitative models ... and banking solutions, powered by The Triumph Network. Founded in 2010, the company is ...

Bank of America

Data Scientist II

Charlotte, NC · On-site

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us! What we're building: The data science team (within GPS) is working on more than ...

Bank of America

Data Scientist II

New York, NY · On-site

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us! What we're building: The data science team (within GPS) is working on more than ...

TBK Bank, SSB

Director of Data Science

Dallas, TX · On-site

Director of Data Science Position Summary We are seeking a Director of Data Science to design, build, and operationalize quantitative models that power both internal and customer-facing intelligence ...

TBK Bank, SSB

Director of Data Science

Dallas, TX · On-site

Director of Data Science Position Summary We are seeking a Director of Data Science to design, build, and operationalize quantitative models that power both internal and customer-facing intelligence ...

SoFi

Senior Manager, Data Science

Manhattan, NY · On-site

SoFi is a next-generation financial services company and national bank that is transforming personal finance. They are seeking a Senior Manager of Data Science to lead a team of Data Scientists ...

Bank of America

Data Scientist I

Charlotte, NC · On-site

Bank of America is committed to helping make financial lives better through every connection. The Data Scientist I role within the Global Payment Solutions team focuses on translating complex data ...

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How much do data science bank jobs pay per year?

As of Jul 14, 2026, the average yearly pay for data science bank 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 Data Scientist in banking, and why are they important?

To thrive as a Data Scientist in banking, you need strong analytical skills, proficiency in statistics, and a solid foundation in mathematics, typically supported by a degree in a quantitative field. Familiarity with programming languages like Python or R, experience with machine learning libraries, and knowledge of data visualization and big data platforms such as SQL, Hadoop, or Spark are crucial. Exceptional problem-solving abilities, attention to detail, and effective communication skills help you translate complex data insights into actionable strategies for non-technical stakeholders. These skills ensure accurate risk assessment, fraud detection, and data-driven decision-making in the highly regulated financial sector.

What is the role of data science in banking?

Data science in banking involves analyzing large datasets to improve decision-making, detect fraud, assess credit risk, and personalize customer services. Data scientists use tools like machine learning and statistical models to optimize operations and develop predictive insights within the financial environment.

Do data scientists work at banks?

Yes, data scientists work at banks to analyze financial data, develop predictive models, and improve decision-making processes. They often use tools like Python, R, and SQL and may require knowledge of finance and machine learning techniques.

What does a Data Science professional do in a bank?

A Data Science professional in a bank leverages data analysis, statistical modeling, and machine learning to solve business problems and improve decision-making. Their work often involves analyzing customer behavior, detecting fraud, assessing credit risk, and optimizing marketing strategies. They collaborate with other departments to turn raw data into actionable insights, ensuring the bank remains competitive and compliant with regulations. By building predictive models and dashboards, they help the bank enhance efficiency, profitability, and customer satisfaction.

What is the salary of a bank data scientist?

A bank data scientist typically earns between $80,000 and $130,000 annually, depending on experience, location, and education. Senior roles or those with specialized skills in machine learning and big data tools can earn higher salaries, often exceeding $150,000.

Is 40 too late for data science?

Data science roles are open to candidates of all ages, and many professionals transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

How does a Data Scientist at a bank typically contribute to cross-functional teams, and what collaboration challenges might they face?

As a Data Scientist in a banking environment, you will frequently collaborate with teams from IT, risk management, marketing, and business strategy to develop data-driven solutions. This might involve translating complex analytical findings into actionable insights for non-technical stakeholders or integrating models into existing business processes. Common challenges include aligning data science objectives with business goals, managing data privacy concerns, and ensuring clear communication across different departments. Building strong relationships and maintaining open communication channels are essential for overcoming these challenges and delivering impactful results.
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Data Science Bank jobs near you

Executive Director - AI Data Science

Career Renew

Santa Monica, CA • On-site

Full-time

Posted 6 days ago

Job description

Job Summary:
Career Renew is recruiting for an Executive Director - AI Data Science to lead high-impact AI and data science initiatives for fixed income and investment banking businesses. The role involves driving enterprise-critical projects, mentoring a team of data scientists, and aligning data science solutions with commercial priorities.
Responsibilities:
• Lead flagship AI/ML projects that drive measurable value across fixed income trading, credit, rates, and investment banking workflows, from pricing and execution to risk and origination.
• Direct the development of models for valuing illiquid instruments, forecasting price and spread movements, modeling prepayment and default risk, and analyzing the yield curve and interest rate dynamics.
• Act as senior technical authority on advanced AI methods (generative AI, causal inference, LLM-based analytics, RAG, simulation) and on their application to quantitative finance.
• Translate complex desk-level and banking challenges into enterprise-grade data science solutions with tangible P&L and risk-adjusted ROI.
• Mentor and guide a small team of data scientists, building technical excellence, modeling rigor, and responsible AI adoption.
• Partner with trading desks, banking coverage teams, risk, MDs, and executive committees to ensure AI initiatives align with firm-wide priorities.
• Represent TWG Global in external technical forums and partnerships with universities, regulators, and technology leaders.
• Define standards for experimentation, reproducibility, and model governance, consistent with the controls expected in a regulated capital markets environment.
• Stay ahead of emerging trends in AI/ML and quantitative finance, advising on adoption and firm-wide capability building.
Qualifications:
Required:
• 10+ years of experience in data science/ML applied to fixed income or capital markets (Mandatory)
• Data science or machine learning background serving enterprise customers and delivering enterprise level impact (Mandatory)
• Led projects in fixed income, capital markets, or quantitative finance (Mandatory)
• Experience mentoring or managing a small data science team (Mandatory)
• Master's or higher in Data Science, Statistics, Computer Science, Financial Engineering, Quantitative Finance, or a related discipline.(Mandatory)
• Deep expertise in ML: advanced machine learning, causal inference, deep learning, statistical modeling, and time series analysis (Mandatory)
• Hands-on technical depth in Python (or R), cloud-based platforms, and modern ML frameworks (Mandatory)
• Working knowledge of fixed income fundamentals: duration, convexity, yield curves, credit spreads, rate models, and the pricing of debt instruments and derivatives (Mandatory)
• Proven ability to influence senior stakeholders (MDs, traders, executives) - must be credible to a very senior, technical audience (Mandatory)
Preferred:
• Experience with Palantir platforms (e.g., Foundry/AIP/Ontology)
• Familiarity with vector databases, knowledge graphs, and LLM application frameworks for advanced analytics
• Cloud or AI/ML certifications (e.g., AWS ML Specialty, Google Cloud ML Engineer, Azure AI Engineer)
Company:
Career Renew aims to transform the job search process by making it easier for candidates Founded in 2022, the company is headquartered in Bucharest, RO, , with a team of 2-10 employees. The company is currently Early Stage.

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