Entry Level Data Analyst

Entry Level Data Analyst at JobGether / Recidiviz — Research Report

Introduction

The Entry Level Data Analyst role at Recidiviz is a full-time, remote-friendly opportunity for candidates who want to use data to improve outcomes in the criminal justice system. The work combines SQL, Python, research, visualization, and partner communication rather than focusing only on dashboards or routine reporting.

The listed deadline is not listed, so applicants should treat the position as time-sensitive and apply while the posting remains active. Recidiviz lists annual compensation of $85,000 and accepts candidates with at least six months of practical experience, including internships, research, and qualifying part-time work.

This role can be particularly valuable early in a career because analysts work with complex real-world datasets and see how analysis influences products, state programs, and policy decisions. It is a strong fit for someone who wants technical growth while contributing to safer and healthier communities.

Overview of JobGether / Recidiviz

JobGether is associated with remote-job discovery and hiring information, while Recidiviz is the organization connected to the specific Data Analyst opening. Recidiviz is a mission-driven technology nonprofit that works with state criminal justice agencies to understand incarceration patterns and support evidence-based improvements.

Its niche sits at the intersection of civic technology, public policy, data engineering, and social impact. Rather than selling conventional business intelligence software, Recidiviz develops data systems, analyses, and tools that help partners identify drivers of incarceration and improve outcomes for people moving through prisons and supervision programs.

The organization works with raw and processed criminal justice data from multiple states, government reports, policy documents, and operational information. Its analysts help transform inconsistent source material into reliable insights that can support state partners and internal product teams.

Recidiviz appears designed for people who value mission alignment, ownership, and close collaboration. The listed role is remote within the United States, with optional access to offices in Oakland and Manhattan. Travel to state partners is encouraged approximately once per year and may occasionally be required, including visits to prisons and parole offices.

Entry Level Data Analyst Role

Role Overview

The Entry Level Data Analyst supports experienced analysts and cross-functional teammates on well-defined analytical projects. Day-to-day work may include inspecting source data, cleaning tables, writing SQL queries, analyzing patterns, building visualizations, and preparing data required for product launches.

The role has a direct operational impact. A careful analysis can reveal where people are being held longer than necessary, identify gaps in supervision data, or help a state partner understand whether a policy is producing the expected result. The analyst is not merely preparing numbers; they are helping make complex systems more understandable and actionable.

Detailed Responsibilities

• Explore raw and processed criminal justice datasets to identify patterns, inconsistencies, and missing information.
• Write SQL queries using joins, aggregations, filters, and window functions.
• Use Python and Pandas to clean, reshape, analyze, and visualize data.
• Perform well-scoped analyses under the guidance of senior analysts.
• Build clear visualizations with existing internal tools.
• Prepare state-specific datasets for product launches and operational workflows.
• Compare findings against source data and documentation to verify accuracy.
• Translate analytical results into concise explanations for teammates and external partners.
• Review policy documents, agency reports, and other non-database sources for context.
• Collaborate with product, engineering, and policy-oriented colleagues.

Day-to-Day Workflow

A typical morning may begin with a team check-in, project updates, and clarification of the question the analysis must answer. The analyst could then inspect a new extract, review table definitions, and write a preliminary SQL query to understand the size, completeness, and structure of the data.

The afternoon may involve cleaning records in Python, investigating an unexpected result, or creating a visualization for an internal review. Before sharing the work, the analyst would typically validate totals, document assumptions, check edge cases, and explain limitations. Strong performance depends as much on careful investigation as on producing a technically correct query.

Tools and Technologies

The clearest technical requirements are SQL and Python, specifically the Pandas package for data analysis and visualization. Candidates should also expect to work with spreadsheets, version-controlled files, documentation systems, and visualization tools already used by the organization.

Because the work involves multiple states and data sources, analysts should be comfortable learning unfamiliar schemas quickly. Familiarity with Git, notebooks, data-quality checks, relational databases, and dashboard principles would strengthen an application, even when those tools are not explicitly listed.

Skills and Requirements

Technical Skills

• Working proficiency in SQL, including joins, aggregations, and window functions.
• Practical Python experience, especially with Pandas.
• Ability to clean, reshape, and validate messy real-world datasets.
• Basic statistical reasoning and comfort interpreting trends.
• Ability to create readable charts and explain what they show.
• Understanding of data quality, reproducibility, and documentation.
• Interest in public-sector, policy, or criminal justice data.

Recidiviz requests at least six months of practical experience exploring, analyzing, and cleaning real-world datasets. Internships, academic research, and part-time roles can count when their hours approximate six months of full-time experience.

Soft Skills

Communication is central because analysts work with internal teams and external state partners. Candidates must be able to explain a finding without hiding behind technical language, ask precise questions, and acknowledge uncertainty when the data does not support a definitive conclusion.

• Curiosity about how data is generated and recorded.
• Attention to detail when checking source records and calculations.
• Comfort receiving feedback from experienced teammates.
• Reliability in remote collaboration.
• Empathy when working with sensitive criminal justice information.
• Patience with ambiguous or incomplete datasets.

Experience Expectations

A polished portfolio is more valuable than a long list of tools. Include one project that demonstrates SQL joins and aggregations, another that shows Python data cleaning, and a short explanation of how you validated the results.

A criminal justice project is not required, but candidates should demonstrate responsible analytical judgment. A public dataset involving housing, health, education, transportation, or public safety can work well if the project explains data limitations and avoids overstating conclusions. The posting does not identify a GPA requirement, so evidence of applied skill should take priority.

Salary and Benefits

The listed annual compensation is $85,000 for the Entry Level Data Analyst position. That figure is competitive for an early-career remote data analyst role, particularly given the mission-driven environment and the opportunity to work with complex public-sector data.

Reported benefits include 90% medical, dental, and vision coverage, flexible time off with 20 days of paid time off, three paid volunteer days, and 13 paid holidays. The package also includes 12 weeks of paid parental leave, a 401(k) plan with a 5% company match and no vesting period, One Medical membership, a monthly ClassPass credit, and mental health support through Talkspace.

The role is remote for workers in the United States, with optional office access in Oakland and Manhattan. The posting does not promise automatic full-time conversion because the position itself is full-time. Candidates should ask about growth paths, promotion expectations, professional development funding, and how remote analysts receive mentorship.

JobGether Hiring Process

Step-by-Step Hiring Stages

1. Application: Submit a tailored resume emphasizing SQL, Python, data cleaning, and applied analysis.
2. Screening: A recruiter or hiring team member may discuss experience, location, compensation, mission interest, and work authorization.
3. Assignment: Candidates may be asked to complete a practical analysis or discuss a previous project.
4. Interviews: Expect conversations about technical reasoning, collaboration, communication, and interest in criminal justice data.
5. Offer: Finalists receive compensation and employment details, including remote-work expectations and possible travel.

Application Timeline

No application deadline is listed, so submitting early is sensible. A realistic process for a specialized nonprofit data role may take two to six weeks, depending on interview scheduling, assignment review, and team availability. Keep a copy of every submitted document because later interviews may refer directly to the resume or portfolio.

Screening Methods

Applicant tracking systems and human reviewers will likely look for exact terms such as SQL, Python, Pandas, data cleaning, data visualization, research, and stakeholder communication. Put these skills in context rather than listing them in isolation.

A strong resume bullet might state that you used SQL and Python to clean 500,000 records, created validation checks, and reduced manual reporting time by 30%. Quantified outcomes help reviewers understand both the scale and the value of your work.

Interview Preparation

Example Interview Questions

• Tell us about a time you found a quality problem in a dataset. How did you investigate and resolve it?
• How would you use SQL to identify the most recent record for each person or case?
• Describe an analysis where the initial result changed after you examined the source data more closely.
• How would you explain an uncertain finding to a state partner or nontechnical teammate?

How to Answer

Use the STAR method for behavioral questions: describe the situation, define your task, explain the actions you took, and finish with the result. For technical questions, narrate your assumptions before writing a query. Explain how you would check duplicates, null values, date logic, and denominator choices.

For mission-related questions, avoid vague statements about wanting to “help people.” Discuss why reliable data matters in public systems and show that you understand the ethical risks of drawing conclusions from incomplete or biased records.

What Recruiters Evaluate

• Whether you can work independently without becoming isolated.
• Whether your SQL knowledge extends beyond basic filtering.
• Whether you inspect data rather than trusting the first output.
• Whether you communicate limitations clearly.
• Whether you can learn a specialized domain quickly.
• Whether your interest in the mission is informed and genuine.

How to Get Selected

Practical Tips

• Tailor the resume to emphasize applied SQL and Python work near the top.
• Prepare a two-minute explanation of your strongest data project.
• Show validation steps, not just final charts.
• Read about incarceration, parole, sentencing, and data privacy before interviews.
• Practice explaining one technical result to a nontechnical audience.
• Be transparent about work authorization because visa sponsorship is not available.

Common Mistakes To Avoid

• Submitting a generic business analyst resume with no SQL examples.
• Presenting dashboards without explaining the underlying data model.
• Ignoring duplicate records, missing values, or inconsistent dates.
• Using jargon instead of clearly stating the practical conclusion.
• Overclaiming social impact from a small or biased sample.
• Failing to mention experience with messy, imperfect datasets.

How To Stand Out

Create a concise portfolio case study using a public dataset. Include the question, data source, SQL logic, Python workflow, validation checks, visualization, and limitations. A reviewer should be able to see not only that you can produce an answer, but that you know when the answer may be unreliable.

Networking can help when it is specific and respectful. Reach out to current or former Recidiviz employees with a focused question about analyst collaboration, onboarding, or the organization’s data challenges. Do not ask for a referral immediately; demonstrate that you have read the role and thought seriously about the mission.

Final Thoughts

The Recidiviz Entry Level Data Analyst role offers an unusually direct connection between technical work and public impact. Candidates who combine SQL fundamentals, Python practice, careful data validation, and thoughtful communication will be better positioned than applicants who simply list popular analytics tools.

Because the deadline is not listed, prepare a targeted application now. Lead with practical evidence, explain your reasoning clearly, and show that you can treat sensitive data with both rigor and care.

Frequently Asked Questions

What Is The Salary?

The listed compensation is $85,000 annually for the Entry Level Data Analyst role. Benefits reportedly include health coverage, paid time off, parental leave, a 5% 401(k) match, wellness support, and mental health resources.

How Competitive Is Hiring?

The role is likely competitive because it offers remote flexibility, mission-driven work, and a clearly defined entry-level compensation package. Candidates can improve their odds by showing at least six months of hands-on data experience and demonstrating SQL beyond simple queries.

Which Skills Matter Most?

The most important skills are SQL, Python with Pandas, real-world data cleaning, visualization, quality checking, and communication. Curiosity about criminal justice data and the ability to explain findings responsibly are equally important to technical proficiency.