DAY TO DAY:
Our client, a digital trading firm based out of Chicago, is seeking a highly analytical and self-directed Business Intelligence & Market Quality Analyst to help us transform complex trading, client, and operational data into actionable business insights.
This role will be responsible for analyzing market quality, market share, liquidity provider performance, client behavior, product performance, and broader company KPIs. The ideal candidate is comfortable working independently with large and complex datasets, building automated reporting, and translating data into clear recommendations for senior leadership.
Our data environment currently includes Looker and Amazon Redshift. The right candidate should be able to autonomously pull data, validate data quality, build repeatable reporting, investigate trends, and identify opportunities to improve business performance.
This is a high-impact role for someone who enjoys working at the intersection of data, markets, operations, and strategy.
Key Responsibilities
- Analyze market quality across trading products, venues, liquidity providers, and client segments.
- Evaluate market maker performance, including quote quality, spread competitiveness, uptime, depth, fill quality, and responsiveness.
- Measure and report on market share, volume trends, client activity, liquidity trends, and revenue drivers.
- Build, maintain, and improve dashboards and reporting in Looker.
- Write and optimize SQL queries against Redshift and other data sources.
- Create automated reports for leadership, sales, trading, operations, risk, and product teams.
- Identify meaningful trends, anomalies, and opportunities within trading and business datasets.
- Translate complex data into clear, concise insights and recommendations.
- Partner with internal stakeholders to define KPIs, reporting requirements, and analytical frameworks.
- Develop repeatable processes for recurring business reviews, market quality reviews, client performance reviews, and board-level reporting.
- Improve data quality by identifying inconsistencies, missing fields, unreliable metrics, or gaps in existing reporting.
- Support ad hoc analyses for strategic initiatives, client conversations, liquidity provider evaluations, and product launches.
- Build scalable analytical models and reporting processes that reduce manual work over time.
- Proactively investigate business questions without requiring step-by-step direction.