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Remote Data Analyst Jobs in Chester, VA (NOW HIRING)

Xtreme Solutions Inc

Azure Data & MLOps Engineer

Petersburg, VA · Remote

$112K - $134K/yr

... Analytics/AI Program Schedule: Full-Time / 1.0 FTE Work Arrangement: Primarily Remote with Required ... The Azure Data & MLOps Engineer will build the Azure data pipelines, integrations, deployment ...

Genworth Financial

Lead Data Architect

Richmond, VA · On-site +1

... remote applicants residing in states/locations in the following states: Virginia, North Carolina ... Strong analytical, problem-solving, and critical thinking skills needed for data modeling

Lantern

Strategy Analyst

Richmond, VA · Remote

This is a remote-first role with occasional (~1x month) travel. Responsibilities and Duties ... Analyze claims and cost savings data to drive insights for reporting and product improvement

Truist

Process Analyst II

Richmond, VA · On-site +1

$74K - $134K/yr

Richmond, VA - 1001 Semmes Avenue No Full Remote/Telecommute. No Relocation Assistance. ESSENTIAL ... data collection plan in support of projects led by Process Engineers 4. Assist with providing ...

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All JobsData Analyst JobsRemote Data Analyst JobsRemote Data Analyst Jobs in Chester, VA

Remote Data Analyst information

See Chester, VA salary details

$31.3K

$76K

$125.2K

How much do remote data analyst jobs pay per year?

As of Sep 7, 2026, the average yearly pay for remote data analyst in Chester, VA is $76,047.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,500.00 and $89,300.00 per year, depending on experience, location, and employer.

What does a remote data analyst do?

A Remote Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed business decisions, all while working from a location outside of a traditional office. They use statistical tools and software to interpret complex datasets, identify trends, and generate reports. Remote Data Analysts collaborate with team members via digital communication platforms and often present their findings to stakeholders to guide strategy and operations. Their work is essential in industries such as finance, healthcare, marketing, and technology, where data-driven decisions are crucial.

What does a remote data analyst do?

Remote data analysts use a range of methods to chart, examine, and analyze data for their clients. Unlike in-house data analysts, remote data analysts, work from home or a different location outside of the office. As a remote data analyst, your job is to evaluate a company’s data using a combination of mathematical inspection, transformation, and modeling techniques to simplify and condense it. Once the analysis is complete, you create reports for management to use to make critical decisions; this is why remote data analysts need to confirm the accuracy of the data. You may also need to present your reports to stakeholders.

What are the key skills and qualifications needed to thrive as a remote data analyst?

To thrive as a Remote Data Analyst, you need strong analytical skills, proficiency in statistics, and a degree in a quantitative field such as mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and visualization platforms such as Tableau or Power BI is typically required. Excellent communication, self-motivation, and time management are crucial soft skills for collaborating remotely and presenting insights effectively. These skills ensure accurate data-driven decision-making and effective remote teamwork in a digital work environment.

How do remote data analysts typically collaborate with team members and stakeholders given the virtual work environment?

Remote Data Analysts often rely on digital communication tools such as Slack, Microsoft Teams, and Zoom to stay connected with colleagues and stakeholders. They participate in regular virtual meetings, share dashboards or reports via cloud-based platforms, and provide data-driven insights to support decision-making. Successful remote analysts proactively communicate their findings, clarify requirements, and coordinate with cross-functional teams such as IT, marketing, or finance to ensure alignment on project goals and deliverables.

What is the difference between Remote Data Analyst vs Remote Data Scientist?

AspectRemote Data AnalystRemote Data Scientist
Required CredentialsBachelor's in Data, Statistics, or related field; often certifications in Excel, SQL, or TableauBachelor's or Master's in Data Science, Computer Science, or related; certifications in Python, R, machine learning
Work EnvironmentPrimarily office-based or remote, focusing on data analysis and reportingPrimarily remote, involving complex data modeling and predictive analytics
Employer & Industry UsageUsed across finance, marketing, healthcare, and retail sectorsCommon in tech, finance, and research industries

Remote Data Analysts focus on interpreting data, creating reports, and supporting decision-making, while Remote Data Scientists develop models, perform advanced analytics, and work on predictive insights. Both roles require strong analytical skills, but Data Scientists typically have more technical expertise in programming and machine learning.

Are remote data analyst jobs still in demand?

Remote data analyst jobs remain in high demand due to the increasing reliance on data-driven decision making across industries. Skills in data visualization, SQL, and statistical analysis are particularly valuable, and many companies continue to expand their remote analytics teams to access a broader talent pool.

Can I get remote jobs as a remote data analyst?

Remote data analyst positions are widely available and often require skills in data analysis tools like Excel, SQL, and Python. Many companies offer remote roles with flexible schedules, and candidates typically need a strong analytical background and good communication skills.

Can you work remotely as a remote data analyst?

Remote data analysts can often work from home or other locations, depending on the employer’s policies. Many companies offer remote positions that require skills in data analysis tools like Excel, SQL, or Python, and a reliable internet connection. Availability of remote work varies by organization and role requirements.
More about Remote Data Analyst jobs

What are the most commonly searched types of Data Analyst jobs in Chester, VA?

The most popular types of Data Analyst jobs in Chester, VA are:

What job categories do people searching Remote Data Analyst jobs in Chester, VA look for?

The top searched job categories for Remote Data Analyst jobs in Chester, VA are:

What cities near Chester, VA are hiring for Remote Data Analyst jobs?

Cities near Chester, VA with the most Remote Data Analyst job openings:

Remote Data Analyst jobs near you
Infographic showing various Remote Data Analyst job openings in Chester, VA as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $76,047 per year, or $36.6 per hour.

Lead Data Architect AI/ML (W2)

Digital Links Inc

Glen Allen, VA • Remote

Contractor

Re-posted 21 days ago

Job description

Role: Lead Data Architect AI/ML

Location: Remote
6-month contract to FTE
 
Lead Data Architect who will define and drive the data and AI architecture strategy for a Workplace Solutions division within the insurance domain. This role leads the design of modern cloud-based data platforms, machine learning operations, and governance frameworks that support enterprise analytics, intelligent automation, and AI innovation. Day to day, this person will create architecture roadmaps, guide Agile Release Trains (ARTs), partner with business leaders, and operationalize scalable, secure, and ethical data ecosystems.
Top 4 Skills
  • Enterprise Data Architecture (cloud-native, AWS preferred)
  • Distributed data systems (warehouse / lakehouse)
  • MLOps & ML lifecycle management (SageMaker, MLflow)
  • Python, SQL, Snowflake, MongoDB
Responsibilities
Data & AI Architecture Leadership
  • Design and evolve enterprise-scale data platforms and AI architecture
  • Enable analytics, ML, and intelligent automation across the division
  • Architect distributed data systems in microservices and event-driven environments
Strategy & Roadmapping
  • Define data modernization and AI strategy aligned to business goals
  • Develop long-term roadmaps for MLOps, governance, and AI enablement
  • Translate business strategies into measurable data solutions
AI & ML Enablement
  • Lead AI prototypes, POCs, and production of ML pipelines
  • Operationalize models using containers, APIs, and serverless frameworks
  • Establish CI/CD for ML and model observability practices
Data Engineering & Modeling Standards
  • Oversee ETL/ELT architecture from source to target
  • Define logical and physical data modeling standards (dimensional, normalized, denormalized)
  • Support BI, analytics, and AI data access patterns
Governance & Responsible AI
  • Establish data quality, lineage, and trust frameworks
  • Promote ethical AI, explainability, and regulatory compliance
  • Implement observability and governance best practices
Leadership & Influence
  • Guide architecture across Agile Release Trains (ARTs)
  • Influence cross-functional stakeholders and enterprise architects
  • Mentor engineers and data professionals
Qualifications
Required:
  • 5+ years leading enterprise data architecture initiatives
  • Expertise in distributed data systems and lakehouse/warehouse architecture
  • Experience with ML operationalization frameworks (MLflow, SageMaker, similar)
  • Strong Python, SQL, Snowflake, MongoDB skills
  • AWS cloud experience (Glue, Redshift, SageMaker, Bedrock preferred)
  • ETL/ELT design and implementation experience
  • Strong logical and physical data modeling expertise
  • Experience in microservices and event-driven architecture
  • Knowledge of data governance, explainability, and responsible AI
  • Familiarity with CI/CD for ML, data observability, and lineage tools
  • TOGAF Certification
  • Demonstrated strategic vision, roadmapping, and executive influence
Nice to Have:
  • Group Benefits or insurance industry experience
  • Kafka, Spark, real-time analytics experience
  • Data mesh familiarity
  • Direct AI development experience