Remote Staff Analyst Jobs
Remote staff analyst jobs are in active demand across the U.S., with remote-first firms and distributed teams hiring across technology, government contracting, healthcare, and financial services. Employers actively hiring remote staff analysts right now include Lockheed Martin, Angi, and jamf. Find a role that fits below and apply directly.
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About Us
Overview
You own the data foundation behind how CX Operations understands its performance and how it connects to the broader Fanatics ecosystem. As the Staff Analyst for Ops Ecosystem Analytics, you design and build the architecture, models, and operating standards that make CX Ops ecosystem data in Snowflake trustworthy, scalable, and usable by cross-functional teams, leaders, and by the AI agents we're building on top of it.
This is a hands-on technical role with broad influence. You take raw tables from across the business and turn them into clean, documented, tested models that the rest of the team builds on. You work side by side with Data & Analytics Engineering as well as Strategy teams. You set the SQL and data-modeling bar for the Ops Analytics team without managing anyone. You tell the story of what the data says, regularly presenting to senior leadership and translating architecture decisions and analytical findings into impact they can act on.
We are building toward an AI-first way of operating, and this role is central to it. The right person is technically sharp, relentlessly detail-oriented, and curious about both what the data is saying and how AI changes the way we find and act on answers. You move fast, own ambiguous problems, and hold yourself to a high bar without being told to.
What You'll Do
Data architecture and operations environment
- Own the architecture of CX Ops ecosystem data in Snowflake, including schema design, data layers, access patterns, and the operating model that keeps it reliable as it scales.
- Decide how ecosystem Ops data should be structured, owned, and governed, and drive alignment with necessary teams, like Data Engineering, on those decisions.
- Consolidate overlapping or one-off datasets into shared, well-governed sources of truth, and set naming and documentation conventions.
- Define and track data quality standards for Ops ecosystem data.
- Build alerting on critical metrics as needed so issues are caught before they reach leadership reporting.
dbt and analytics engineering
- Turn raw cross-domain tables into clean, tested, reusable dbt models that the whole team can build on.
- Own the team's core models and introduce data tests, code review practices, and modeling standards that catch issues before they reach stakeholders.
- Review teammates' SQL, models, and dashboards for correctness, performance, and readability, and coach analysts on best practices.
- Replace manual, one-off data pulls with automated, always-on solutions.
Analytical work and insights
- Lead complex, cross-functional analyses from an ambiguous business problem through scoping, analysis, and a decision-ready recommendation, without formal authority over contributors.
- Diagnose root causes rather than symptoms, and surface trends, anomalies, and risks without waiting to be asked.
- Support scenario analysis and impact sizing for product initiatives, operational changes, and staffing decisions.
- Set the standard for publication-ready dashboards and reporting, with clearly defined KPIs and documented assumptions.
Communication and influence
- Present findings, architecture decisions, and impact to Ops and senior leadership. Take a high-uncertainty situation and communicate what you know, what you don't, and what you recommend.
- Build the narrative around the data so stakeholders understand not just what the numbers say but what to do about them.
- Mentor and support analysts across the team through standards, reviews, and knowledge sharing.
AI enablement
- Make sure agents are built on validated, trusted data foundations, and contribute the data models and evaluation rigor they need before they move to build.
- Track the performance of deployed agents against Ops goals.
- Bring a point of view on where AI can be trusted in analytical workflows and where human judgment needs to stay in the loop.
Required Qualifications
- 5+ years in analytics, analytics engineering, business intelligence, or strategic operations.
- Advanced, hands-on SQL. You write, QA, and optimize complex queries and set the standard others are held to. This role includes a live, on-screen technical exercise.
- Strong dbt experience. You have designed model layers, written tests, and made sound architectural decisions, not just maintained existing models.
- Demonstrated experience designing or owning a data environment in a cloud data warehouse (Snowflake preferred), including schema design, governance, and data quality.
- Experience working closely with data or analytics engineering teams to turn raw data into production-ready models.
- Strong executive communication. You have presented analysis and recommendations to senior leaders and can defend your methodology under scrutiny.
- Experience owning complex, cross-functional projects end to end.
- Experience building dashboards in Sigma, Tableau, or a comparable tool.
- High attention to detail. You catch data quality issues before they surface in leadership reporting.
- Comfortable in fast-paced, ambiguous environments with shifting priorities.
Preferred Qualifications
- Experience supporting AI/ML workflows, agent builds, or automation initiatives.
- Python or a similar scripting language for data manipulation and automation.
- Familiarity with operational KPIs across customer support, fraud, payments, or workforce management.
- Experience in gaming, fintech, or sports, or another operationally intensive, high-volume environment.
- Bachelor's degree in Analytics, Computer Science, Statistics, Economics, or a related field.
Depending on the role, your interview and onboarding experience may include in-person components, such as onsite interviews or Launching into Better: LIVE—a multi-day cultural immersion in New York City for full-time, non-seasonal hires. These sessions are designed to build connection and bring our culture to life, though specific travel and participation requirements will be confirmed based on your role and location. Your recruiter will provide clear guidance at each stage of the process.
For information about our benefits, please visit https://benefitsatfanatics.com/
By submitting your application, you agree to our terms of service and acknowledge you have read our Candidate Privacy Policy.
Fanatics will never ask candidates for money, banking information, or other sensitive personal information as part of the interview process. If you receive a suspicious message claiming to be from Fanatics recruiting, please do not respond and report it here.
About Us
Overview
You own the data foundation behind how CX Operations understands its performance and how it connects to the broader Fanatics ecosystem. As the Staff Analyst for Ops Ecosystem Analytics, you design and build the architecture, models, and operating standards that make CX Ops ecosystem data in Snowflake trustworthy, scalable, and usable by cross-functional teams, leaders, and by the AI agents we're building on top of it.
This is a hands-on technical role with broad influence. You take raw tables from across the business and turn them into clean, documented, tested models that the rest of the team builds on. You work side by side with Data & Analytics Engineering as well as Strategy teams. You set the SQL and data-modeling bar for the Ops Analytics team without managing anyone. You tell the story of what the data says, regularly presenting to senior leadership and translating architecture decisions and analytical findings into impact they can act on.
We are building toward an AI-first way of operating, and this role is central to it. The right person is technically sharp, relentlessly detail-oriented, and curious about both what the data is saying and how AI changes the way we find and act on answers. You move fast, own ambiguous problems, and hold yourself to a high bar without being told to.
What You'll Do
Data architecture and operations environment
- Own the architecture of CX Ops ecosystem data in Snowflake, including schema design, data layers, access patterns, and the operating model that keeps it reliable as it scales.
- Decide how ecosystem Ops data should be structured, owned, and governed, and drive alignment with necessary teams, like Data Engineering, on those decisions.
- Consolidate overlapping or one-off datasets into shared, well-governed sources of truth, and set naming and documentation conventions.
- Define and track data quality standards for Ops ecosystem data.
- Build alerting on critical metrics as needed so issues are caught before they reach leadership reporting.
dbt and analytics engineering
- Turn raw cross-domain tables into clean, tested, reusable dbt models that the whole team can build on.
- Own the team's core models and introduce data tests, code review practices, and modeling standards that catch issues before they reach stakeholders.
- Review teammates' SQL, models, and dashboards for correctness, performance, and readability, and coach analysts on best practices.
- Replace manual, one-off data pulls with automated, always-on solutions.
Analytical work and insights
- Lead complex, cross-functional analyses from an ambiguous business problem through scoping, analysis, and a decision-ready recommendation, without formal authority over contributors.
- Diagnose root causes rather than symptoms, and surface trends, anomalies, and risks without waiting to be asked.
- Support scenario analysis and impact sizing for product initiatives, operational changes, and staffing decisions.
- Set the standard for publication-ready dashboards and reporting, with clearly defined KPIs and documented assumptions.
Communication and influence
- Present findings, architecture decisions, and impact to Ops and senior leadership. Take a high-uncertainty situation and communicate what you know, what you don't, and what you recommend.
- Build the narrative around the data so stakeholders understand not just what the numbers say but what to do about them.
- Mentor and support analysts across the team through standards, reviews, and knowledge sharing.
AI enablement
- Make sure agents are built on validated, trusted data foundations, and contribute the data models and evaluation rigor they need before they move to build.
- Track the performance of deployed agents against Ops goals.
- Bring a point of view on where AI can be trusted in analytical workflows and where human judgment needs to stay in the loop.
Required Qualifications
- 5+ years in analytics, analytics engineering, business intelligence, or strategic operations.
- Advanced, hands-on SQL. You write, QA, and optimize complex queries and set the standard others are held to. This role includes a live, on-screen technical exercise.
- Strong dbt experience. You have designed model layers, written tests, and made sound architectural decisions, not just maintained existing models.
- Demonstrated experience designing or owning a data environment in a cloud data warehouse (Snowflake preferred), including schema design, governance, and data quality.
- Experience working closely with data or analytics engineering teams to turn raw data into production-ready models.
- Strong executive communication. You have presented analysis and recommendations to senior leaders and can defend your methodology under scrutiny.
- Experience owning complex, cross-functional projects end to end.
- Experience building dashboards in Sigma, Tableau, or a comparable tool.
- High attention to detail. You catch data quality issues before they surface in leadership reporting.
- Comfortable in fast-paced, ambiguous environments with shifting priorities.
Preferred Qualifications
- Experience supporting AI/ML workflows, agent builds, or automation initiatives.
- Python or a similar scripting language for data manipulation and automation.
- Familiarity with operational KPIs across customer support, fraud, payments, or workforce management.
- Experience in gaming, fintech, or sports, or another operationally intensive, high-volume environment.
- Bachelor's degree in Analytics, Computer Science, Statistics, Economics, or a related field.
Depending on the role, your interview and onboarding experience may include in-person components, such as onsite interviews or Launching into Better: LIVE—a multi-day cultural immersion in New York City for full-time, non-seasonal hires. These sessions are designed to build connection and bring our culture to life, though specific travel and participation requirements will be confirmed based on your role and location. Your recruiter will provide clear guidance at each stage of the process.
For information about our benefits, please visit https://benefitsatfanatics.com/
By submitting your application, you agree to our terms of service and acknowledge you have read our Candidate Privacy Policy.
Fanatics will never ask candidates for money, banking information, or other sensitive personal information as part of the interview process. If you receive a suspicious message claiming to be from Fanatics recruiting, please do not respond and report it here.
See All 17 Remote Staff Analyst Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote Staff Analyst JobsRemote Staff Analyst Job Market
Who's Hiring
Top Industries Hiring
- Banking & Financial Services
- Consulting & Professional Services
What Employers Look For
The qualifications that appear most often in remote staff analyst jobs.
- Bachelor's degree in business, public policy, finance, economics, or a related field
- Proficiency in Excel or Google Sheets for data analysis and reporting
- Experience building reports or dashboards in SQL, Tableau, or Power BI
- Strong written communication skills for policy memos, briefings, or executive summaries
- Two or more years of analytical experience in a corporate, government, or consulting environment
- Familiarity with project management workflows and cross-functional stakeholder coordination
Tips for Your Remote Staff Analyst Job Search
Apply early to remote roles that fit
Migrate Mate lists remote staff analyst openings from across the U.S. in one place, so you can find roles that match your background and apply directly without sorting through unrelated listings.
Show async communication skills upfront
Remote staff analyst employers screen for structured written communication before the first interview. Use your resume summary and cover letter to demonstrate you can frame analysis clearly in writing, since that skill drives day-to-day work on distributed teams.
Build a remote-ready analysis portfolio
Create two or three self-contained analysis projects using real datasets and publish them where hiring managers can review them independently. Remote employers want evidence you can scope, execute, and present analytical work without hands-on direction.
Target remote-first companies specifically
Companies built around distributed work from the start have clearer processes for onboarding and managing remote staff analysts. Look for organizations that document workflows, use collaborative tools like Confluence or Notion, and explicitly describe themselves as remote-first in job postings.
Remote Staff Analyst Jobs: Frequently Asked Questions
How do I get a remote staff analyst job?
Target companies that already operate distributed teams, since they have the infrastructure and culture to support remote staff analysts from day one. Remote employers screen heavily for self-direction, structured written communication, and comfort with async workflows. Strong candidates demonstrate proficiency in tools like Excel, SQL, or Tableau alongside a clear record of delivering analysis independently without close supervision.
Which companies hire remote staff analysts?
Remote staff analyst roles are posted by Lockheed Martin, Angi, and jamf and others right now, based on current remote listings on Migrate Mate as of November 2026. The employers most active in this space tend to be remote-first technology firms, distributed consulting organizations, and healthcare and financial services companies with geographically spread teams.
Can you get a remote staff analyst job with no experience?
Yes, but remote entry-level staff analyst roles are more competitive because employers expect you to manage your own workload without in-person guidance from day one. You can open the door by building a portfolio of independent data projects, completing relevant certifications in Excel or SQL, and demonstrating strong written communication skills that translate directly to async remote environments.
Do you need a degree for remote staff analyst jobs?
Not always. Many remote employers care more about demonstrated analytical skills and real project results than a specific credential. A portfolio showing quantitative analysis, experience with reporting tools, and the ability to communicate findings clearly in writing can carry significant weight, particularly at technology companies and remote-first firms that evaluate candidates on output over pedigree.
Which industries hire the most remote staff analysts?
The sectors hiring the most remote staff analysts are Banking & Financial Services and Consulting & Professional Services, based on current remote listings on Migrate Mate as of November 2026. These industries concentrate remote staff analyst hiring because their distributed teams depend on analysts who can synthesize data and deliver clear recommendations without requiring on-site collaboration.
See All 17 Remote Staff Analyst Jobs
Find roles that match your experience and apply in just a few clicks.
Find Remote Staff Analyst Jobs