Business Intelligence Analyst

Role overview

A Chicago-based digital trading firm is looking for a self-directed Business Intelligence & Market Quality Analyst who can turn complex trading, client, and operations data into practical insights. The role sits at the intersection of data, markets, operations, and strategy, and requires someone comfortable working independently with large datasets, building automated reporting, and presenting clear recommendations to senior leadership.

What you will do

• Study market quality across trading products, venues, liquidity providers, and client groups.
• Assess liquidity provider and market maker performance, including quote quality, spread competitiveness, uptime, depth, fill quality, and responsiveness.
• Track and report on market share, trading volume patterns, client activity, liquidity movement, and revenue drivers.
• Build, maintain, and enhance dashboards and reports in Looker.
• Develop and tune SQL queries for Redshift and other data sources.
• Produce automated reporting for leadership, sales, trading, operations, risk, and product teams.
• Spot trends, anomalies, and business opportunities in trading and commercial datasets.
• Convert complex findings into concise recommendations and business-facing insights.
• Work with internal stakeholders to define KPIs, reporting needs, and analysis frameworks.
• Create repeatable processes for regular business reviews, market quality reviews, client performance reviews, and board-level reporting.
• Strengthen data quality by finding inconsistencies, missing values, unreliable metrics, and reporting gaps.
• Handle ad hoc analysis for strategic initiatives, client discussions, liquidity provider reviews, and product launches.
• Build scalable analytical models and reporting workflows that reduce manual effort over time.
• Proactively explore business questions without needing detailed step-by-step direction.

Experience and skill requirements

• At least 3 years of experience as a business intelligence analyst, ideally in a financial trading environment.
• Strong ability to analyze revenue, market quality, and trading data and draw actionable conclusions.
• Degree in a math-related field such as financial engineering, mathematics, statistics, or computer science is required.
• Advanced proficiency in Python and SQL.
• Strong SQL knowledge, including joins, aggregations, window functions, CTEs, and query optimization.
• Hands-on experience with BI/reporting tools such as Looker, Tableau, Power BI, Mode, Sigma, or similar platforms.
• Ability to independently extract, clean, validate, analyze, and interpret data.
• Experience with cloud data warehouses such as Amazon Redshift, Snowflake, BigQuery, or Databricks is preferred.
• Background in financial markets, trading, exchanges, market making, brokerage, crypto, fintech, or capital markets is preferred.
• Knowledge of market structure topics such as bid/ask spreads, top-of-book, depth-of-book, liquidity, slippage, fill rates, order books, execution quality, and market share is preferred.
• Experience analyzing liquidity provider, market maker, or execution quality data is preferred.
• Exposure to executive reporting, board reporting, or investor-facing metrics is preferred.
• Experience working with product, sales, trading, risk, compliance, or operations teams is preferred.
• Comfort working with incomplete datasets and creating practical solutions without waiting for perfect infrastructure.
• Master’s degree in a math-related discipline is a plus.
• Experience with Looker plus trading is a plus.
• Experience with Redshift and Postgres is a plus.

Additional context

The company operates with Looker and Amazon Redshift in its current data environment. The ideal hire will be able to independently pull data, check quality, build repeatable reporting, investigate trends, and identify ways to improve business performance.

Location and employment

This is a full-time onsite role based in Chicago, Illinois.