- Competitive pay
- New York, NY, USA
- Permanent, Full time
- FactSet Research Systems Inc
- 23 Oct 17 2017-10-23
FactSet (NYSE:FDS | NASDAQ:FDS) delivers superior analytics, service, content, and technology to help more than 88,000 users see and seize opportunity sooner. We are committed to giving investment professionals the edge to outperform, with fresh perspectives, informed insights, and the industry-leading support of our dedicated specialists. We're proud to have been recognized with multiple awards for our analytical and data-driven solutions and repeatedly ranked as one of Fortune's 100 Best Companies to Work For and a Best Workplace in the United Kingdom and France. Subscribe to our thought leadership blog to get fresh insight delivered daily at insight.factset.com
The Quantitative Risk Research team is responsible for building risk models used as a part of FactSet platform by institutional investment managers worldwide. The risk modeling effort is based on large and diverse market datasets collected and stored by various FactSet groups. We are looking for a data engineer who will play a key role in designing, building and maintaining the data-warehousing for the team. The candidate must have deep knowledge of modern data paradigms and the tools needed for architecture, design, and management of very large datasets, and the ability and aptitude for applying these tools.
• Design, construct, install, test and maintain highly scalable data management systems
• Integrate new data management technologies and software engineering tools into existing structures
• Recommend ways to improve data reliability, efficiency and quality
• Collaborate with research team members on project goals
• Approximately 5yrs of experience working with large datasets, data storage, and statistical analysis
• MS/PhD in a quantitative filed (statistics preferred)
• Previous experience managing projects focused on extracting, merging, analyzing and managing large sets of data across multiple databases
• Deep knowledge of relational databases. Ability to develop highly efficient databases to hold large, complicated data structures. Knowledge of SQL language
• Good understanding of database design and architecture principles;
• Knowledge of data processing techniques, statistical data cleaning and analysis.
• Knowledge of Python and C++
• Being able to work autonomously, collaborate with others to clarify requirements and collect data from multiple sources, and develop, refine, and scale data management procedures, systems, and workflows.
• Strong written and verbal communication skills;
• Knowledge of finance is not required
To find out more about opportunities at FactSet, visit us at www.factset.com/careers, www.facebook.com/factset, or www.twitter.com/factset.