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Exchange Fee Data Analyst (Financial Services)

Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
Exchange Fee Data Analyst (Financial Services): Analyzing trade data, exchange fees, and market data costs while building reports, dashboards, and data models with an accent on trading performance, fee reconciliation, and data quality. Focus on translating business requirements into data solutions, resolving complex financial data issues, and applying advanced analysis techniques to capital markets data.

Location: On-site in Bala Cynwyd, Pennsylvania, in the Philadelphia area

Company

Susquehanna is a global quantitative trading firm using scientific research, engineering, machine learning, and advanced quantitative analysis to develop systematic trading strategies.

What you will do

  • Analyze trade data to identify trends, patterns, and anomalies across electronic trading activities.
  • Calculate, reconcile, and validate exchange fees and market data costs.
  • Build and maintain reports, dashboards, and visualizations for trading performance and cost analysis.
  • Develop robust data models supporting financial and trade data analysis.
  • Translate business requirements into data solution designs and collaborate with stakeholders to improve data quality and processes.

Requirements

  • At least 5 years of experience in the financial services sector.
  • Strong understanding of trade data, asset classes, trade flows, electronic trading, and the trade lifecycle.
  • Knowledge of exchange fee structures, market data fees, and fee calculation and reporting complexities.
  • Proficiency in data analysis, statistical analysis, data cleaning, and modeling.
  • Strong SQL skills and experience with data visualization tools such as Tableau or Power BI.
  • Understanding of investment banking, capital markets, derivatives, and complex financial problem-solving.

Nice to have

  • Degree in finance, economics, data science, or a related field.
  • Experience with Python or R for complex analysis.
  • Knowledge of regulatory requirements and industry standards related to trade data and exchange fees.
  • Project management and cross-functional team leadership experience.
  • Experience applying machine learning and AI to financial data analysis.

Culture & Benefits

  • Non-hierarchical, casual, collaborative environment focused on continuous development.
  • Relaxed dress code and fully stocked kitchens with meals, snacks, and beverages.
  • Access to a 40,000-square-foot fitness facility, on-site wellness center, and on-site services.
  • Discounts for dining, entertainment, shopping, travel, and attractions.
  • Social events and opportunities to support the community through sponsored events and donation drives.

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