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Bank Python Jobs in Washington (NOW HIRING)

World Bank

Risk Officer

Washington, DC · On-site

The World Bank Group is a unique global partnership of five institutions driven by a bold vision to ... Independently build, maintain, and enhance independent benchmark quantitative models using Python ...

Capital One

Lead Data Engineer (Bank Tech)

Mclean, VA · On-site

$103K - $136K/yr

Lead Data Engineer (Bank Tech) Do you love building and pioneering in the technology space? Do you ... Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases ...

Capital One

Lead Data Engineer (Bank Tech)

Mclean, VA · On-site

Lead Data Engineer (Bank Tech) Do you love building and pioneering in the technology space? Do you ... Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases ...

Capital One

Lead Data Engineer (Bank Tech)

Mclean, VA · On-site

$103K - $136K/yr

Lead Data Engineer (Bank Tech) Do you love building and pioneering in the technology space? Do you ... Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases ...

The World Bank Group

Data Analyst

Washington, DC · On-site

The World Bank Group is a unique global partnership of five institutions driven by a bold vision to ... Python, or R. Contribute to the development, testing, and documentation of predictive models ...

Tekcel8

Gen AI

Washington, DC · On-site

... Python · Experience with Large Language Models (LLMs) including GPT, Claude, Gemini, Llama, or ... AI · Experience in Banking, Healthcare, Insurance, Retail, or Manufacturing domains ...

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Bank Python information

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How much do bank python jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for bank python in Washington is $66.39, according to ZipRecruiter salary data. Most workers in this role earn between $54.71 and $75.43 per hour, depending on experience, location, and employer.

How do Python developers in banking typically collaborate with other teams, such as risk management or data analysis?

Python developers in banking frequently work in cross-functional teams, collaborating closely with professionals from risk management, data analysis, and operations. They often translate complex business requirements into efficient, automated solutions, such as risk assessment models or data pipelines. Regular meetings, code reviews, and joint project planning are common practices to ensure alignment and compliance with regulatory standards. This collaborative environment not only enhances the quality of deliverables but also provides developers with a broader understanding of banking operations.

What is a Bank Python?

A Bank Python is not a recognized job title within the banking or technology industries. It may refer to a Python developer working in a bank, responsible for building, maintaining, or automating financial applications using the Python programming language. These professionals help streamline banking operations, develop algorithms for financial analysis, and ensure secure data processing. Their work is crucial for enhancing efficiency and accuracy in banking systems.

What is the difference between Bank Python vs Bank Data Analyst?

AspectBank PythonBank Data Analyst
Required CredentialsPython programming skills, possibly certifications in data analysis or programmingDegree in finance, economics, or data analysis; certifications like CFA or data analytics certifications
Work EnvironmentTech-focused teams within banks, working on automation, data processing, and software developmentFinancial institutions, analyzing data to inform business decisions, reporting, and risk assessment
Industry UsageUsed for automating banking processes, developing financial models, and data managementUsed for interpreting financial data, creating reports, and supporting strategic decisions

Bank Python professionals focus on programming and automation within banking systems, while Bank Data Analysts interpret financial data to guide business strategies. Both roles are vital in modern banking but differ in skill sets and daily tasks.

What are the key skills and qualifications needed to thrive as a Bank Python developer?

To thrive as a Bank Python Developer, you need strong programming skills in Python, expertise in financial data analysis, and a relevant degree in computer science or a related field. Familiarity with SQL databases, version control systems like Git, and experience with financial software or regulatory compliance tools are typically required. Attention to detail, problem-solving abilities, and effective communication are important soft skills that help in collaborating with cross-functional teams and ensuring accuracy. These skills and qualities are crucial to efficiently develop reliable banking applications, maintain system integrity, and adapt to the fast-evolving financial technology landscape.
What are popular job titles related to Bank Python jobs in Washington? For Bank Python jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Bank Python jobs in Washington look for? The top searched job categories for Bank Python jobs in Washington are:
What cities in Washington are hiring for Bank Python jobs? Cities in Washington with the most Bank Python job openings:
Bank Python jobs near you
Infographic showing various Bank Python job openings in Washington as of August 2026, with employment types broken down into 83% Full Time, 16% Part Time, and 1% Contract. Highlights an 94% Physical, 3% Hybrid, and 3% Remote job distribution, with an average salary of $138,100 per year, or $66.4 per hour.

WBG Pioneer - AI Data Engineer Intern

The World Bank Group

Washington, DC • On-site

Internship

Posted 27 days ago

Job description

Every World Bank-financed project depends on systems that track how money is spent, how risk is managed, and how communities are protected. ITSFD builds those systems-this internship is a chance to work on them directly.

Background/Organizational Context

The World Bank Group (WBG) finances development projects across the globe through three distinct institutions, the International Bank for Reconstruction and Development and the International Development Association (IBRD/IDA), the International Finance Corporation (IFC), and the Multilateral Investment Guarantee Agency (MIGA). The Information and Technology Solutions (ITS) Vice Presidency of the World Bank Group delivers a wide portfolio of technology products and services that enable the WBG's development mission. Within ITS, the Fiduciary Operations unit (ITSFD) is responsible for digital solutions that support Procurement, Financial Management, and Environmental and Social Safeguards across World Bank operations. 

About the Team: Procurement

The Procurement team sits within ITS Fiduciary Operations (ITSFD) and is responsible for the digital systems that support procurement activities across World Bank-financed projects. Its flagship platform is STEP (Systematic Tracking of Exchanges in Procurement), an end-to-end online system used for procurement planning, tracking, and document management across the full procurement lifecycle; from planning through contract management. STEP is used by Task Team Leaders, Procurement Specialists, and borrowers alike and supports transparency and accountability through machine-readable reporting and open contracting data. 

The intern will gain hands-on experience in how a global institution plans and  validates data migration for a complex platform modernization. The role offers exposure to agile delivery, data governance, QA practices, UAT preparation, stakeholder coordination, and the practical realities of moving from legacy systems to a modern digital platform.

Duties and Responsibilities
  • Collect data from databases, APIs, cloud storage, files, and other sources.
  • Clean and transform raw data by handling missing values, duplicates, incorrect formats, and outliers, and build and maintain ETL/ELT pipelines using Python, SQL, and data-engineering tools.
  • Perform data validation and quality checks to ensure accuracy and consistency.
  • Work with large datasets using platforms such as Snowflake, Databricks, Spark, or cloud services.
  • Create and maintain data tables, schemas, feature datasets, and data documentation.
  • Assist with feature engineering for machine-learning models.
  • Support vector databases, embeddings, and Retrieval-Augmented Generation pipelines for generative AI applications.
  • Collaborate with data engineers, data scientists, ML engineers, and software developers.
  • Participate in code reviews, team meetings, testing, and technical documentation.

Apply