Client Service Analyst Jobs in District of Columbia
Client Service Analyst jobs in District of Columbia draw from one of the most active markets in the country, concentrated in federal contracting, financial services, and policy-adjacent consulting firms that dominate the D.C. economy across every seniority level from entry-level associates to senior analysts. Most hiring is in Washington D.C. proper, with additional activity in nearby Arlington and Bethesda, where employers like Booz Allen Hamilton, Deloitte, and Bank of America maintain significant operations. The most in-demand specialties are government account management, financial client advisory, and data-driven relationship analysis. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 47+ Client Service Analyst jobs
About the Role
As an Associate Client Data Engineer at CredLens, you will focus on the client-onboarding workflow that brings new credential-issuer data into our platform. You will learn the platform and the fundamentals of production data engineering with direct support from more senior engineers, and gain hands-on experience across the full onboarding workflow, with a clear path to grow into a broader data-engineering role over time. Because so much of the work involves direct client interaction, excellent customer-service skills and clear communication are essential.
This is an early-career, hands-on role focused exclusively on onboarding: partnering directly with clients to receive their data, understanding and documenting the data structure, and cleaning, transforming, and validating the data so it is ready for CredLens' data pipeline. This is an excellent opportunity to start a data career from the ground level by continuing to build a data engineering skillset while working in a role that directly impacts end users. You will work within a small, cohesive Data Engineering team, reporting to the Data Engineering Team Lead. The team is based in Washington, DC. This is a hybrid role requiring in-person attendance at the office at least two days a week, likely Tuesdays and Thursdays.
Note: this is not a "big data" or "real-time" analytics role. It best suits a mission-aligned individual who cares about using data to create more equitable outcomes and who focuses on quality, reliability, and a smooth client experience.
Context
CredLens is building a nonprofit national data trust focused on verified outcomes for non-degree credentials. The effort is an initiative launched by the Strada Education Foundation in 2024. CredLens will deliver actionable insights and power ongoing research for industry-based, professional, and workforce credentials.
CredLens is designed to fill the data gap for non-degree credentials. The attainment of these credentials is growing, but there is little to no data tracking their outcomes. CredLens will offer tailored data analytics and visualizations to credential issuers, workforce training providers, philanthropic funding partnerships, and state system partnerships to support the continuous improvement of credential quality and to support informed funding and scaling decisions.
Key Responsibilities
Core responsibility areas, listed below with the approximate time required for execution in the first 12 - 18 months of work if the incumbent is new to the role:
Serve as the data engineering point of contact for new clients during onboarding, guiding them through what data to provide and in what format.
Receive incoming client data and perform exploratory data analysis to understand its structure, quality, and completeness.
Identify and flag missing, malformed, or inconsistent fields early, and coordinate with the client to resolve them.
Clean, transform, and validate client data so it conforms to CredLens' standards and is ready for downstream ingestion.
Build and run the models and transformations that move a client's data through the onboarding stages of the pipeline, using SQL, Python, DBT, and Airflow.
Document each client's onboarding: data sources, decisions made, and any exceptions, contributing to shared onboarding procedures and templates.
Track onboarding progress and time, and surface areas of friction to improve the process so that it becomes faster and more repeatable over time.
Work with the broader Data Engineering team to research, learn, and implement new improvements to the onboarding pipeline’s efficiency & scalability so it can grow with us.
Qualifications and Experience
Education
Bachelor's degree in computer science, information systems, data science, or a related field is required. OR, equivalent practical experience is required, at least two years.
Experience Required
Suitable for a new or recent graduate; no prior professional experience required. Internships, academic projects, or other hands-on data work are a plus, as is a demonstrated ability to learn quickly.
Working proficiency in SQL and Python for data manipulation and analysis.
Some past experience working with and cleaning raw datasets.
Strong customer-service orientation and the ability to communicate clearly with non-technical clients.
Attention to detail, particularly around data quality, validation, and documentation.
Consistently takes initiative to learn and try new things, and keeps a mindset of constant improvement.
Experience Preferred
Exposure to Redshift, Snowflake, PostgreSQL, or similar databases.
Experience with Pandas DataFrames, Jupyter notebooks, and other quick data processing tools.
Familiarity with DBT, Airflow, or other data pipeline and orchestration tooling.
Familiarity with AWS S3 and Lambda functions, or other AWS services.
Experience working with Github, or another code version control platform.
Experience handling sensitive or confidential data and following security best practices.
Experience working in a startup, nonprofit, or mission-driven environment.
Skills Required
SQL
Python
Data cleaning & manipulation
Interpersonal skills
About CredLens
Non-degree credentials are reshaping how people move from learning to earning. Millions of learners are pursuing certificates, bootcamps, and workforce programs as pathways to better jobs and higher wages. But growth has outpaced clarity.
Thousands of offerings, uneven definitions, and fragmented outcomes data make it nearly impossible to distinguish impact from activity. When results are unclear, learners carry the risk, strong programs can't stand out, and investment can't reliably flow to what works.
CredLens exists to fix that.
We are a neutral, trusted source of high-quality outcomes data for non-degree credentials — connecting issuer-verified credential records to real-world employment, earnings, and education outcomes. Our partners use that data to improve programs, guide investment, and strengthen career pathways for learners.
Two years in, we have a firmly established platform, a growing client base, and the backing of Strada Education Foundation. We are not a startup finding its footing. We are a company beginning to scale — and we are building the team that will take us there.
Mission and Value Alignment
Travel Requirements
Approximately 5% domestic travel anticipated.
plus annual bonus
About the Role
As an Associate Client Data Engineer at CredLens, you will focus on the client-onboarding workflow that brings new credential-issuer data into our platform. You will learn the platform and the fundamentals of production data engineering with direct support from more senior engineers, and gain hands-on experience across the full onboarding workflow, with a clear path to grow into a broader data-engineering role over time. Because so much of the work involves direct client interaction, excellent customer-service skills and clear communication are essential.
This is an early-career, hands-on role focused exclusively on onboarding: partnering directly with clients to receive their data, understanding and documenting the data structure, and cleaning, transforming, and validating the data so it is ready for CredLens' data pipeline. This is an excellent opportunity to start a data career from the ground level by continuing to build a data engineering skillset while working in a role that directly impacts end users. You will work within a small, cohesive Data Engineering team, reporting to the Data Engineering Team Lead. The team is based in Washington, DC. This is a hybrid role requiring in-person attendance at the office at least two days a week, likely Tuesdays and Thursdays.
Note: this is not a "big data" or "real-time" analytics role. It best suits a mission-aligned individual who cares about using data to create more equitable outcomes and who focuses on quality, reliability, and a smooth client experience.
Context
CredLens is building a nonprofit national data trust focused on verified outcomes for non-degree credentials. The effort is an initiative launched by the Strada Education Foundation in 2024. CredLens will deliver actionable insights and power ongoing research for industry-based, professional, and workforce credentials.
CredLens is designed to fill the data gap for non-degree credentials. The attainment of these credentials is growing, but there is little to no data tracking their outcomes. CredLens will offer tailored data analytics and visualizations to credential issuers, workforce training providers, philanthropic funding partnerships, and state system partnerships to support the continuous improvement of credential quality and to support informed funding and scaling decisions.
Key Responsibilities
Core responsibility areas, listed below with the approximate time required for execution in the first 12 - 18 months of work if the incumbent is new to the role:
Serve as the data engineering point of contact for new clients during onboarding, guiding them through what data to provide and in what format.
Receive incoming client data and perform exploratory data analysis to understand its structure, quality, and completeness.
Identify and flag missing, malformed, or inconsistent fields early, and coordinate with the client to resolve them.
Clean, transform, and validate client data so it conforms to CredLens' standards and is ready for downstream ingestion.
Build and run the models and transformations that move a client's data through the onboarding stages of the pipeline, using SQL, Python, DBT, and Airflow.
Document each client's onboarding: data sources, decisions made, and any exceptions, contributing to shared onboarding procedures and templates.
Track onboarding progress and time, and surface areas of friction to improve the process so that it becomes faster and more repeatable over time.
Work with the broader Data Engineering team to research, learn, and implement new improvements to the onboarding pipeline’s efficiency & scalability so it can grow with us.
Qualifications and Experience
Education
Bachelor's degree in computer science, information systems, data science, or a related field is required. OR, equivalent practical experience is required, at least two years.
Experience Required
Suitable for a new or recent graduate; no prior professional experience required. Internships, academic projects, or other hands-on data work are a plus, as is a demonstrated ability to learn quickly.
Working proficiency in SQL and Python for data manipulation and analysis.
Some past experience working with and cleaning raw datasets.
Strong customer-service orientation and the ability to communicate clearly with non-technical clients.
Attention to detail, particularly around data quality, validation, and documentation.
Consistently takes initiative to learn and try new things, and keeps a mindset of constant improvement.
Experience Preferred
Exposure to Redshift, Snowflake, PostgreSQL, or similar databases.
Experience with Pandas DataFrames, Jupyter notebooks, and other quick data processing tools.
Familiarity with DBT, Airflow, or other data pipeline and orchestration tooling.
Familiarity with AWS S3 and Lambda functions, or other AWS services.
Experience working with Github, or another code version control platform.
Experience handling sensitive or confidential data and following security best practices.
Experience working in a startup, nonprofit, or mission-driven environment.
Skills Required
SQL
Python
Data cleaning & manipulation
Interpersonal skills
About CredLens
Non-degree credentials are reshaping how people move from learning to earning. Millions of learners are pursuing certificates, bootcamps, and workforce programs as pathways to better jobs and higher wages. But growth has outpaced clarity.
Thousands of offerings, uneven definitions, and fragmented outcomes data make it nearly impossible to distinguish impact from activity. When results are unclear, learners carry the risk, strong programs can't stand out, and investment can't reliably flow to what works.
CredLens exists to fix that.
We are a neutral, trusted source of high-quality outcomes data for non-degree credentials — connecting issuer-verified credential records to real-world employment, earnings, and education outcomes. Our partners use that data to improve programs, guide investment, and strengthen career pathways for learners.
Two years in, we have a firmly established platform, a growing client base, and the backing of Strada Education Foundation. We are not a startup finding its footing. We are a company beginning to scale — and we are building the team that will take us there.
Mission and Value Alignment
Travel Requirements
Approximately 5% domestic travel anticipated.
plus annual bonus
See All 47 Client Service Analyst Jobs in District of Columbia
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Find Client Service Analyst JobsClient Service Analyst Jobs by City in District of Columbia
Where District of Columbia roles are concentrated, by current openings.
Client Service Analyst Job Market in District of Columbia
A snapshot from current District of Columbia openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Fintech
- Staffing & Recruiting
- Technology & Software
- Banking & Financial Services
- Investment & Asset Management
What District of Columbia Employers Look For
The qualifications that appear most often in client service analyst jobs across District of Columbia.
- Bachelor's degree in business, finance, economics, or a related field required
- Experience managing client accounts or supporting relationship managers preferred
- Proficiency with CRM platforms such as Salesforce or Microsoft Dynamics expected
- Strong written and verbal communication skills for client-facing interactions required
- Familiarity with federal contracting processes or government client environments valued
- Analytical skills to interpret data and prepare client reports and presentations required
Client Service Analyst Jobs in District of Columbia: Frequently Asked Questions
How do you become a client service analyst in District of Columbia?
Most employers in District of Columbia hire client service analysts with a bachelor's degree in business, finance, or a related field, and no state-issued license is required for the role itself. Candidates pursuing roles in federally regulated financial services may need FINRA Series licenses depending on the employer. Entry-level positions at D.C.-based consulting firms and federal contractors often prefer candidates with internship experience or familiarity with government account environments.
Which companies hire client service analysts in District of Columbia?
Companies currently hiring client service analysts in District of Columbia include Global Impact, Microchip Technology, and Cox Communications, per current listings on Migrate Mate as of July 2026. D.C.'s deep concentration of federal contractors, financial institutions, and management consulting firms means demand for this role stays consistent throughout the year.
Which District of Columbia cities have the most client service analyst jobs?
Washington account for the most client service analyst openings in District of Columbia. Washington D.C. itself drives the majority of postings given its density of consulting firms, financial services companies, and federal agencies, while Arlington and Bethesda attract strong demand from large contractors and financial institutions headquartered along the northern Virginia and Maryland corridors.
Are there remote client service analyst jobs in District of Columbia?
Yes, and they are more common than in many fields. About 73% of client service analyst openings tied to District of Columbia are remote or hybrid as of July 2026, reflecting how well the desk-based and communication-focused nature of the role adapts to distributed work. Account coordination, reporting, and client communication tasks are the parts of the role most frequently performed remotely.
How can I get hired as a client service analyst in District of Columbia with little or no experience?
The most realistic entry path is applying to associate or junior analyst roles at D.C.-area federal contractors and consulting firms, which regularly run structured new-graduate programs for candidates without direct experience. Booz Allen Hamilton, Deloitte, and similar firms headquartered in the D.C. area post rotational and entry-level cohort positions each year. Adjacent roles like client services coordinator, account support specialist, or administrative analyst are common stepping stones, and earning a CRM or project management certification gives candidates a measurable edge in a competitive applicant pool.
Where can I find and apply to client service analyst jobs in District of Columbia?
You can find and apply to client service analyst jobs in District of Columbia on Migrate Mate, which lists current openings tied to the D.C. market. Search the listings, identify the roles that match your experience and target employers, and apply directly to the ones that fit your background.
See All 47 Client Service Analyst Jobs in District of Columbia
Find roles in District of Columbia that match your experience and apply in just a few clicks.
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