Remote Entry Level Data Analytics Jobs

Remote Entry Level Data & Analytics Jobs at Built In Chicago — Research Report

Introduction

Remote entry level data and analytics jobs at Built In Chicago appeal to candidates who want early-career experience with real business impact, not just classroom exercises. For job seekers targeting a Built In Chicago internship or first job in analytics, this type of role can build a strong foundation in reporting, dashboarding, experimentation, and stakeholder communication while keeping the flexibility of remote work. The deadline for this opportunity is not mentioned, so the smartest move is to apply quickly once a relevant role appears.

What makes this path especially valuable is the combination of visibility and versatility. Entry-level analysts who can translate messy data into clear decisions are often the people teams rely on most, and that kind of exposure can accelerate growth faster than a narrow, isolated role.

Overview of Built In Chicago

Built In Chicago is part of the Built In network, a media and recruiting platform focused on tech jobs, employer branding, and local hiring markets. In practice, it serves two audiences at once: companies that need qualified candidates and job seekers who want a clearer view of tech employers, salary benchmarks, and open roles. Its Chicago presence matters because the city is one of the strongest Midwest hubs for fintech, healthtech, SaaS, logistics, retail tech, and data-heavy companies.

In the local talent market, Built In Chicago competes indirectly with large job boards, niche recruiting platforms, and employer career sites, but its niche is sharper: curated technology jobs with a strong editorial layer. That combination gives it an edge for candidates who want roles that are more relevant than broad, keyword-heavy listings. For employers, the platform is attractive because it reaches candidates who already self-identify as tech-adjacent or tech-focused.

The company’s key services include job listings, employer profiles, salary data, recruiting visibility, and content around hiring and workplace trends. Its market presence is strongest in tech-centered hiring, especially for companies trying to attract digital, analytics, product, and engineering talent. That reputation makes Built In Chicago a familiar starting point for candidates researching where to apply and what compensation looks like in the market.

People want to work through or around Built In Chicago because the ecosystem is built around career momentum. Employers using the platform often care about modern tools, hybrid or remote flexibility, and data-driven decision-making. For candidates, that can translate into roles that value curiosity, communication, and practical analytics skills over pedigree alone.

Remote Entry Level Data & Analytics Jobs

Role Overview

A remote entry level data and analytics role typically supports business teams by cleaning datasets, building recurring reports, and helping leaders understand trends they can act on. In the Built In Chicago job ecosystem, these roles often sit in BI, product analytics, marketing analytics, or operations analytics, depending on the employer. The day-to-day work is usually a mix of SQL queries, spreadsheet analysis, dashboard updates, and written summaries.

The business impact is straightforward: better decisions, faster. When entry-level analysts catch a data issue, spot a conversion drop, or surface a customer behavior trend, they help teams move from guesswork to evidence. That’s why these roles are often seen as high-trust apprenticeships that can lead to stronger analyst, analytics engineer, or data science paths later.

Detailed Responsibilities

• Pull, clean, and validate data from internal systems and reporting databases.
• Write SQL queries to answer business questions and create repeatable reports.
• Maintain dashboards that track KPIs such as traffic, conversion, retention, revenue, or engagement.
• Support ad hoc analysis requests from product, marketing, sales, or operations teams.
• Document metric definitions so teams use consistent logic across reports.
• Identify anomalies, gaps, and trends, then explain them in plain English.
• Assist with A/B test readouts, cohort analysis, or funnel analysis.
• Partner with teammates to improve reporting accuracy and reduce manual work.

Day-to-Day Workflow

A realistic day starts with checking dashboards and incoming requests. If a report failed overnight or a metric moved unexpectedly, the analyst usually investigates first, then communicates what changed and whether it matters. After that, the focus shifts to a mix of ticket-based work and project work, often with a few meetings to clarify business context.

Most entry-level analysts spend part of the day in SQL, part in Excel or Google Sheets, and part in a BI tool like Tableau, Power BI, or Looker. The best performers are not the fastest typists; they are the people who ask precise questions, verify assumptions, and write clean summaries that non-technical teammates can actually use.

Tools and Technologies

Remote analytics roles commonly use SQL, Excel, Google Sheets, Tableau, Power BI, Looker, and sometimes Python or R for deeper analysis. Depending on the employer, the role may also involve dbt, Snowflake, BigQuery, Redshift, or Databricks. Project tracking and collaboration usually happen in Slack, Jira, Asana, Notion, or Monday.com.

For an entry-level candidate, fluency matters more than breadth. Hiring managers want someone who can query a dataset, sanity-check the numbers, and explain the result without overcomplicating it.

Skills and Requirements

Technical Skills

Strong candidates usually know SQL well enough to join tables, filter data cleanly, aggregate metrics, and troubleshoot common logic errors. Spreadsheet confidence still matters too, especially for quick analysis, lookups, pivot tables, and scenario checks. A working understanding of dashboarding tools is a major plus because many teams expect entry-level hires to contribute to reporting quickly.

Basic familiarity with statistics also helps, especially for interpreting averages, percentages, variance, and test results. Python is often helpful rather than mandatory, but it becomes a real advantage when a candidate can use it for data cleaning or lightweight analysis.

Soft Skills

Communication is one of the biggest differentiators in this space. Analysts who can write concise updates, ask focused follow-up questions, and explain a trend without drowning people in jargon tend to move faster.

Problem-solving, reliability, and comfort with ambiguity matter just as much. Entry-level analytics work often starts with an unclear question, a messy dataset, or a stakeholder who does not fully know what they need yet.

Experience Expectations

For a Built In Chicago internship or entry-level opening, employers usually care more about evidence than years of experience. That evidence can come from coursework, internship projects, case studies, academic research, volunteer work, or a personal portfolio. A strong GPA can help, but it rarely carries the application on its own.

Candidates stand out when they can show at least one or two well-documented projects that include the question, the analysis method, the tools used, and the business takeaway. Even a simple dashboard project can be persuasive if it is cleanly presented and clearly explained.

Salary and Benefits

For remote entry-level data and analytics roles tied to the Built In Chicago market, a realistic salary range is usually about $60,000 to $80,000 annually for full-time junior roles, with some stronger employers paying closer to the low-$80,000s depending on stack, industry, and city-adjusted compensation. Internship compensation, when offered, often lands around $20 to $35 per hour, though some highly competitive programs may pay more.

Perks commonly include remote work support, flexible schedules, learning resources, and access to professional development. In the broader Built In Chicago employer ecosystem, benefits advertised by companies can include home-office stipends for remote employees, tuition reimbursement, retirement matching, and health coverage options. Some employers also offer conversion pathways from internship or contract work into full-time roles.

For job seekers, the biggest hidden benefit is skill compounding. A strong remote entry-level analytics role can give you portfolio-worthy experience, internal references, and a faster path into more advanced data work within 12 to 24 months.

Built In Chicago Hiring Process

Step-by-Step Hiring Stages

1. Application: Submit a tailored resume, relevant projects, and any portfolio links.
2. Screening: Recruiters check fit, location requirements, communication skills, and tool familiarity.
3. Assignment: Some employers use a short SQL, dashboard, or case exercise.
4. Interviews: Expect one or more rounds with a recruiter, manager, and cross-functional teammate.
5. Offer: Final compensation, start date, and remote-work details are discussed.

Application Timeline

Applications should go in as soon as possible once a role is live, because strong analytics listings can move quickly. In many cases, the process takes two to four weeks from first contact to offer, though complex hiring cycles can stretch longer if multiple stakeholders are involved. If a deadline is not posted, treating the role as rolling is usually the safest assumption.

Screening Methods

Screening often starts with keyword alignment. Resumes that mention SQL, dashboards, reporting, business metrics, data validation, and a relevant BI tool are more likely to get traction than resumes that only list broad academic experience.

Portfolio quality matters a lot. A simple project page with screenshots, a short summary of the problem, and a few clear takeaways can outperform a cluttered portfolio full of vague claims.

Interview Preparation

Example Interview Questions

• Tell me about a time you used data to solve a problem or influence a decision.
• How would you investigate a sudden drop in a key metric?
• Describe a dashboard or report you built and how people used it.
• What would you do if a stakeholder asked for a metric that does not exist yet?

How to Answer

The strongest answers use the STAR method: situation, task, action, result. Keep the setup brief, spend most of the time on what you did, and end with the outcome or lesson learned. For analytics roles, it also helps to explain how you checked the data, what assumptions you made, and how you handled uncertainty.

If you are asked about a technical problem, walk through your thought process out loud. Interviewers are often evaluating how you reason, not just whether you land on the right answer immediately.

What Recruiters Evaluate

Recruiters usually look for three things first: technical readiness, communication clarity, and genuine interest in the role. Hiring managers then narrow in on analytical judgment, curiosity, and whether you can operate independently in a remote environment.

For remote jobs specifically, self-management matters more than many candidates expect. Teams want proof that you can stay organized, follow through, and ask for help early instead of quietly getting stuck.

How to Get Selected

Practical Tips

Tailor your resume to the exact job title instead of using a general student resume. Put SQL, BI tools, reporting, and any measurable project outcomes near the top where they are easy to see.

Bring one portfolio project that feels relevant to a real business problem. A retention analysis, product funnel dashboard, or marketing performance report usually lands better than an abstract classroom exercise.

Use your application materials to show judgment, not just activity. A hiring team wants to know that you can find the signal, not just produce charts.

Common Mistakes to Avoid

• Submitting a generic resume with no analytics keywords.
• Listing tools you cannot actually use in a live interview.
• Ignoring business context and focusing only on technical steps.
• Sending a portfolio with no explanation of the problem or result.
• Writing answers that sound polished but do not show real analysis.

How to Stand Out

Standout candidates connect the numbers to business decisions. Instead of saying you built a dashboard, explain which decision it helped inform, what changed after people saw it, and how you know it was useful.

Networking helps too, especially in a city-specific ecosystem like Built In Chicago. Engaging with recruiters, alumni, and local analytics professionals can create context before the application is reviewed. A short, thoughtful message often beats a long, generic one.

Finally, make your work easy to skim. Clean formatting, concise bullets, and a focused project narrative signal that you will also communicate well on the job.

Final Thoughts

Remote Entry Level Data & Analytics Jobs at Built In Chicago are a strong launch point for candidates who want practical experience, remote flexibility, and a fast path into real business analytics work. If your goal is to learn how to get hired at Built In Chicago or land a similar entry-level analytics role, focus on SQL, dashboards, business storytelling, and one or two polished projects that prove you can turn data into decisions.

The best next move is simple: build a focused resume, sharpen your portfolio, and apply early. In analytics hiring, the candidates who look prepared usually get the first serious look.

Frequently Asked Questions

Salary Range

The salary for Remote Entry Level Data & Analytics Jobs at Built In Chicago is typically around $60,000 to $80,000 for full-time junior roles, with internships often paying about $20 to $35 per hour. Compensation can rise above that range depending on the company, tooling, and local market alignment.

Competition Level

It is reasonably competitive to get hired at Built In Chicago because the platform sits in a strong tech hiring market and attracts candidates who already care about data, product, and analytics. Applicants with proof of hands-on SQL work, dashboards, or measurable project outcomes usually have a much better chance than candidates with only classroom experience.

Top Skills

The most important skills for this role are SQL, spreadsheet analysis, dashboarding, clear communication, and basic business understanding. If you also know Python, statistics, or a modern BI tool, you will look stronger and more job-ready.