Job description

Connecting clients to markets – and talent to opportunity. With 5,4 0 0 + employees and over 80,000 institutional, commercial, and payment s clients, we operate from more than 8 0 offices spread across six continents. As a Fortune 100, Nasdaq-listed provider, we connect clients to the global markets – focusing on innovation, human connection, and providing world-class products and services to all types of investors. Whether you want to forge a career connecting our retail clients to potential trading opportunities, or ingrain yourself in the world of institutional investing, StoneX Group is made up of four business segments that offer endless potential for progression and growth. Institutional : Immerse yourself in the best-in-class institutional-grade technology, working alongside industry experts and gaining exposure to various asset classes, such as equities, options, fixed income securities, and advanced trading, research, and management technology. Reporting to the Global Head of Institutional Sales, this role will support the organization across enterprise initiatives, establish a consistent framework for client intelligence and sales execution, and connect existing workstreams around shared priorities including client coverage, cross-sell, wallet expansion, prospecting, and sales productivity. The role is hands-on. The successful candidate will independently interrogate data, build and test analyses and models, and develop reporting that turns client, product, transaction, and revenue data into actionable commercial intelligence. The candidate will be expected to work directly with SQL, Power BI, company-approved AI tools such as Copilot or Claude, and related analytics tools to rapidly explore commercial questions, test hypotheses, and develop actionable insights. Just as importantly, this person must be able to validate AI- and model-generated analysis, recognize limitations or inconsistencies in the underlying data, and clearly explain the commercial implications to Sales and senior leadership. This role will not own the underlying technology or data platforms. It will own the commercial requirements and outcomes they are intended to enable—working across Sales Leadership, Product, Data, and Technology to ensure individual initiatives collectively improve how StoneX understands clients, coordinates coverage, identifies opportunities, and grows relationships. Client Intelligence & Analytics • Hands-on analytics. Independently interrogate client, product, transaction, and revenue data using SQL, Power BI, approved AI tools, and related technologies to develop and test segmentation, wallet-share, penetration, cross-sell, and other commercial intelligence • AI-enabled analysis. Use company-approved AI tools such as Copilot or Claude to accelerate data exploration, analysis, research, and development of commercial insights while independently validating outputs and underlying assumptions • Data modeling & business measures. Develop robust data models and commercial measures in Power BI, including client hierarchy, revenue attribution, product penetration, wallet share, pipeline, cross-sell, and sales-performance measures—not simply dashboards and visualizations • Single Client View. Represent Sales in the design and adoption of the enterprise Single Client View, defining commercial requirements for client hierarchy, coverage, products, revenue, transaction activity, interactions, and opportunities • Client intelligence. Combine internal and external data to create actionable insight into client relationships, opportunity, white space, and risk • Segmentation & prioritization. Develop and test client segmentation, wallet-share, propensity, and attrition indicators that help direct coverage toward the highest-value opportunities • Insight to action. Translate analysis into practical sales tools, including account plans, cross-sell opportunities, next-best-product insights, prospect prioritization, and early-warning indicators • Analytical validation. Challenge analytical outputs, identify data-quality or methodology limitations, and determine whether the evidence supports the intended commercial conclusion • Prototype to scale. Develop working analyses and prototypes and partner with enterprise Data and Technology teams to scale successful approaches where appropriate Required • 5+ years of experience in financial services, with experience in sales strategy, sales analytics, client coverage, commercial strategy, or a related role • Working understanding of capital markets, commodities, FX, brokerage, clearing, payments, or other complex financial-services businesses and how they generate revenue • Hands-on SQL proficiency, with the ability to query, join, validate, and analyze client, transaction, product, and revenue datasets • Strong Power BI capability, including experience with data modeling, business measures/DAX, data relationships, and analytical design, in addition to dashboard development and visualization • Demonstrated ability to use enterprise-approved generative AI tools such as Copilot or Claude to accelerate analysis and develop actionable business insights • Ability to critically validate AI-generated analysis, challenge assumptions, recognize data-quality and methodological limitations, and explain their business implications • Ability to independently develop client segmentation, wallet-share, product-penetration, cross-sell, pipeline, and sales-performance analyses • Strong understanding of client data structures, hierarchy, entity resolution, and data quality • Demonstrated ability to connect business strategy with data, technology, and operating-model change • Strong commercial judgment and ability to move comfortably between strategy, analytics, and execution • Excellent communication skills, including the ability to translate complex analysis into clear recommendations for front-office and executivae audiences • Bachelor's degree in business, finance, economics, analytics, or a related discipline Preferred • Python or similar analytical programming experience for data manipulation, automation, modeling, or prototyping • Experience working with modern enterprise data platforms such as Databricks or equivalent • Exposure to predictive analytics, machine learning, or AI applied to sales and client intelligence • Experience with external client/market-intelligence datasets • Experience developing enterprise client hierarchy, coverage, or relationship-management models • Background in sales strategy, business management/COO, commercial analytics, or strategy consulting within financial services Hiring Salary Range $175,000 - $225,000 (Salary to be determined by the education, experience, knowledge, skills and abilities of the applicant, internal equity and alignment with market data.)   Subject to business performance and recommendations of management, this role may be eligible to participate in an incentive compensation plan.  This compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position, is offered. #LI-TA1

Requirements

Must-haves

Connecting clients to markets – and talent to opportunity.
Client Intelligence & Analytics
Client intelligence. Combine internal and external data to create actionable insight into client relationships, opportunity, white space, and risk
Segmentation & prioritization. Develop and test client segmentation, wallet-share, propensity, and attrition indicators that help direct coverage toward the highest-value opportunities
Insight to action. Translate analysis into practical sales tools, including account plans, cross-sell opportunities, next-best-product insights, prospect prioritization, and early-warning indicators
Analytical validation. Challenge analytical outputs, identify data-quality or methodology limitations, and determine whether the evidence supports the intended commercial conclusion
Prototype to scale. Develop working analyses and prototypes and partner with enterprise Data and Technology teams to scale successful approaches where appropriate
5+ years of experience in financial services, with experience in sales strategy, sales analytics, client coverage, commercial strategy, or a related role
Working understanding of capital markets, commodities, FX, brokerage, clearing, payments, or other complex financial-services businesses and how they generate revenue
Hands-on SQL proficiency, with the ability to query, join, validate, and analyze client, transaction, product, and revenue datasets
Strong Power BI capability, including experience with data modeling, business measures/DAX, data relationships, and analytical design, in addition to dashboard development and visualization
Demonstrated ability to use enterprise-approved generative AI tools such as Copilot or Claude to accelerate analysis and develop actionable business insights
Ability to critically validate AI-generated analysis, challenge assumptions, recognize data-quality and methodological limitations, and explain their business implications
Ability to independently develop client segmentation, wallet-share, product-penetration, cross-sell, pipeline, and sales-performance analyses
Strong understanding of client data structures, hierarchy, entity resolution, and data quality
Demonstrated ability to connect business strategy with data, technology, and operating-model change
Strong commercial judgment and ability to move comfortably between strategy, analytics, and execution
Excellent communication skills, including the ability to translate complex analysis into clear recommendations for front-office and executivae audiences

Nice-to-haves

Python or similar analytical programming experience for data manipulation, automation, modeling, or prototyping
Experience working with modern enterprise data platforms such as Databricks or equivalent
Exposure to predictive analytics, machine learning, or AI applied to sales and client intelligence
Experience with external client/market-intelligence datasets
Experience developing enterprise client hierarchy, coverage, or relationship-management models
Background in sales strategy, business management/COO, commercial analytics, or strategy consulting within financial services

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

sqlaipythonmachine learning

Platform: icims
Effort: medium