Data Analyst, Transformative Change – Disputes, Claims & Investigations

Stout•Chicago, NY

About The Position

Stout’s Transformative Change practice combines data analysis, research, strategy, and operational experience to help clients achieve sustainable change in complex environments. It helps clients meet financial objectives, implement strategic initiatives, address compliance requirements, and evaluate impact. Engagements may involve designing, implementing, and improving programs, policies, and operational processes for clients, including government entities and nonprofit organizations. The practice works with nonprofit legal organizations, pro bono counsel, government entities, and court-appointed monitors on matters involving housing, education, disability rights, public benefits, immigration, family and child rights, and related civil rights and system reform issues. As a Data Analyst in the practice, you will turn complex structured and unstructured information into clear, accurate analyses and accessible visualizations. Your work will help teams and clients understand data quality, identify relationships across information sources, and make informed decisions in support of transformative change initiatives. You will translate complex data into understandable visualizations and client-ready findings, support data collection, monitoring, and visualization for collaborative, multi-stakeholder initiatives, and contribute analytical insights to data-driven strategy planning, financial and fiscal impact assessments, and implementation milestones. Stout offers competitive compensation, benefits, and wellness options, along with a culture of inclusion and respect. The firm invests in professional growth through training, mentorship, employee resource groups, and performance feedback. Flexible work schedules and a discretionary time off policy are intended to support work-life balance. The estimated annual compensation range is $60,000 to $130,000, and the role is anticipated to be eligible for an annual bonus plan.

Requirements

Bachelor’s degree in data science, computer science, information technology, mathematics, accounting, economics, finance, or a related field.
1–3 years of experience in data analytics, problem-solving, coding, or related work.
Proficiency with Tableau.
Proficiency in SQL and database management, including table creation, data imports and transformation, coding, and querying.
Experience with ETL processes and working in a team-oriented environment.
Strong attention to detail and the ability to troubleshoot data quality issues, reconcile discrepancies, and ensure data accuracy and completeness.
Strong quantitative and qualitative research skills, with the ability to analyze complex data and financial or operational documents.
Clear communication, ability to manage multiple workstreams independently, and adaptability to evolving priorities and deadlines.

Nice To Haves

Tableau Desktop Specialist or Tableau Certified Data Analyst credential; preferred but not required.
Python programming experience; preferred but not required.

Responsibilities

Identify, normalize, and analyze large structured and unstructured datasets, including data limitations and quality issues.
Assess relationships among multiple data sources and organize information for effective analysis.
Design and implement database models; download, store, and import raw data; and maintain SQL database tables.
Use business intelligence tools, including Tableau, to build visualizations and practical client-facing tools.
Apply complex extract, transform, and load (ETL) processes and SQL querying to prepare and analyze data.
Maintain detailed workpapers documenting assumptions, methodologies, and information sources.
Translate findings from technical analyses into clear, simple terms for non-technical audiences.
Conduct industry and technical research and prepare analyses, reports, and presentations.
Coordinate day-to-day project activities with clients, internal teams, and other engagement professionals.
Communicate project status, timelines, and findings to internal and external stakeholders.
Manage multiple workstreams, adapt to changing priorities and deadlines, and deliver accurate work under tight deadlines.
Review others’ work for quality assurance.
Use analytical judgment and thoughtful visual presentation, including consideration of color, spatial relationships, and data density.
Collaborate, demonstrate initiative, and use technology to solve complex problems.
Provide careful documentation, collaboration, and responsive client service.