Are you passionate about financial services and data analysis? Join our dynamic team as an Exchange Fee Data Analyst and play a pivotal role in shaping the future of trading performance and cost management!
Potential Responsibilities Include:
- Analyzing trade data to identify trends, patterns, and anomalies.
- Calculating, reconciling, and validating exchange fees and market data costs.
- Building and maintaining reports and dashboards related to trading performance and costs.
- Developing and maintaining robust data models to support analysis.
- Translating business requirements into data solution designs.
- Supporting and building visualizations for end-users.
- Collaborating with other teams to improve data quality and processes.
What we're looking for
Key Qualifications and Experience:
- Financial Services Experience: Minimum of 5 years of experience within the financial services sector.
- Trade Data Expertise: Proven understanding and experience with trade data, including various asset classes, trade flows, and the data supporting electronic trading.
- Exchange Fees Knowledge: Familiarity with exchange fee structures, market data fees, and the complexities of fee calculations and reporting for trade data usage.
- Data Analysis Skills: Proficiency in data analysis techniques, including statistical analysis, data cleaning, and modeling.
- Technical Proficiency: Strong SQL skills for querying and data retrieval. Experience with data visualization tools such as Tableau, Power BI, or similar platforms. Familiarity with scripting languages like Python or R for more complex analysis is a plus.
- Financial Acumen: Understanding of financial concepts, including investment banking, capital markets, derivatives, and the trade lifecycle.
- Problem-Solving Abilities: Ability to identify and resolve complex data and financial issues.
- Communication Skills: Excellent written and verbal communication skills, with the ability to effectively communicate findings and insights to both technical and non-technical audiences.
- Collaboration and Proactivity: Experience working effectively within a team environment and collaborating with various stakeholders across different departments.
Preferred Qualifications:
- Degree: Finance, Economics, Data Science, or a related field.
- Industry Knowledge: Deep understanding of regulatory requirements and industry standards related to trade data and exchange fees.
- Project Management: Experience in managing projects and leading cross-functional teams.
- Advanced Technical Skills: Proficiency in advanced data analysis tools and techniques, including machine learning and AI applications in financial data analysis is preferred.
What’s In It For You
- Our non-hierarchical culture allows employees of every level to thrive and make impact. We are not your typical trading firm – the environment is casual, collaborative and we focus on continuous development.
- Relaxed dress code (jeans and sneakers are the norm and team jerseys every Friday)
- Fully stocked kitchens for breakfast, lunch, snacks, and beverages
- A forty thousand square-foot state of the art fitness facility with brand-new equipment, multi-purpose courts, group exercise classes, and locker room spaces
- Discounts for dining, entertainment, shopping, travel, and attractions
- Social events such as a poker tournament, holiday party, company outings, and more
- On-site Wellness Center
- On-site services such as a mailroom, barber, dry cleaning, and car maintenance
- Opportunities to give back to the community through Susquehanna sponsored events and donation drives
About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.
#LI-Onsite
Key Qualifications and Experience:
- Financial Services Experience: Minimum of 5 years of experience within the financial services sector.
- Trade Data Expertise: Proven understanding and experience with trade data, including various asset classes, trade flows, and the data supporting electronic trading.
- Exchange Fees Knowledge: Familiarity with exchange fee structures, market data fees, and the complexities of fee calculations and reporting for trade data usage.
- Data Analysis Skills: Proficiency in data analysis techniques, including statistical analysis, data cleaning, and modeling.
- Technical Proficiency: Strong SQL skills for querying and data retrieval. Experience with data visualization tools such as Tableau, Power BI, or similar platforms. Familiarity with scripting languages like Python or R for more complex analysis is a plus.
- Financial Acumen: Understanding of financial concepts, including investment banking, capital markets, derivatives, and the trade lifecycle.
- Problem-Solving Abilities: Ability to identify and resolve complex data and financial issues.
- Communication Skills: Excellent written and verbal communication skills, with the ability to effectively communicate findings and insights to both technical and non-technical audiences.
- Collaboration and Proactivity: Experience working effectively within a team environment and collaborating with various stakeholders across different departments.
Preferred Qualifications:
- Degree: Finance, Economics, Data Science, or a related field.
- Industry Knowledge: Deep understanding of regulatory requirements and industry standards related to trade data and exchange fees.
- Project Management: Experience in managing projects and leading cross-functional teams.
- Advanced Technical Skills: Proficiency in advanced data analysis tools and techniques, including machine learning and AI applications in financial data analysis is preferred.
What’s In It For You
- Our non-hierarchical culture allows employees of every level to thrive and make impact. We are not your typical trading firm – the environment is casual, collaborative and we focus on continuous development.
- Relaxed dress code (jeans and sneakers are the norm and team jerseys every Friday)
- Fully stocked kitchens for breakfast, lunch, snacks, and beverages
- A forty thousand square-foot state of the art fitness facility with brand-new equipment, multi-purpose courts, group exercise classes, and locker room spaces
- Discounts for dining, entertainment, shopping, travel, and attractions
- Social events such as a poker tournament, holiday party, company outings, and more
- On-site Wellness Center
- On-site services such as a mailroom, barber, dry cleaning, and car maintenance
- Opportunities to give back to the community through Susquehanna sponsored events and donation drives
About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.
#LI-Onsite
From SIG's posting. See the original
