Data Visualization Analyst

Lockton•Chicago, IL

About The Position

The Data Visualization Analyst develops financial and risk scenario models paired with interactive visualizations that empower clients and internal teams to make informed strategic decisions. This role combines quantitative modeling expertise with compelling data visualization to build client-facing tools that tell data stories and drive business impact. The analyst designs, builds, and deploys forecasting models—from scratch—then transforms model outputs into intuitive dashboards and reports that stakeholders can explore and act upon. This is a 50/50 blend of statistical modeling and visualization, with full ownership of the model lifecycle from development through production monitoring.

Requirements

Bachelor's degree in Finance, Economics, Data Science, Statistics, Mathematics, Business Analytics, or a related field.
2–5 years of professional experience in financial modeling, data analysis, business intelligence, or analytics.
Proficiency with Python, R, or both for data manipulation, statistical analysis, and modeling.
Strong SQL skills—ability to write efficient queries, work with relational databases, and manage complex datasets.
Experience building forecasting or scenario models (e.g., regression, time-series, Monte Carlo simulations, or financial projections).
Hands-on experience with Tableau, Power BI, or similar business intelligence and visualization platforms.
Strong analytical and problem-solving skills; ability to translate business questions into quantitative solutions.
Excellent written and verbal communication skills; ability to explain technical concepts to both technical and non-technical audiences.

Nice To Haves

Experience with financial modeling, risk analysis, or scenario planning in professional settings.
Familiarity with version control systems (Git) and collaborative development practices.
Experience deploying models to production and monitoring performance in live environments.
Background in consulting, insurance, healthcare, or financial services.
Knowledge of data visualization best practices and design principles for analytical dashboards.
Experience with statistical testing, hypothesis validation, or model evaluation techniques.

Responsibilities

Design and build financial forecasting and risk modeling solutions using Python, R, and SQL to help clients understand potential outcomes and make strategic decisions.
Develop scenario models (e.g., revenue forecasts, financial projections, risk assessments) from requirements gathering through validation, ensuring accuracy and business alignment.
Extract, transform, and prepare large datasets using SQL and Python/R to support modeling workflows.
Validate model outputs, document assumptions and methodologies, and communicate technical details to both technical and non-technical stakeholders.
Deploy models to production environments, establish monitoring protocols, and maintain model performance over time.
Transform financial models and scenario outputs into interactive dashboards and reports using Tableau, Power BI, or similar tools that allow clients to explore results and test assumptions.
Design intuitive user interfaces that guide clients through model scenarios and clearly communicate insights, risks, and opportunities.
Build dynamic, client-facing analytical tools that integrate model logic with visualization—enabling teams to adjust inputs and see real-time output changes.
Support model deployment to business intelligence platforms and ensure visualizations remain accurate as underlying models are updated or refined.
Partner with internal consulting and account teams to understand client requirements, translate business questions into modeling objectives, and iterate on solutions.
Monitor production models for data quality issues, performance drift, or accuracy concerns; troubleshoot and document incidents.
Maintain clear documentation of model logic, assumptions, data sources, and visualization design decisions for knowledge retention and handoffs.
Contribute to team knowledge-sharing, best practices, and process improvements in financial modeling and analytics tooling.