New York, NY, USA
FactSet’s product suite of smart analytics and unique data empower the world’s leading financial service professionals to make more informed decisions every day. At our heart is an inclusive community unified by the spirit of going above and beyond. Our philosophy is to embrace diversity, and that our best ideas can come from anyone, anywhere, at any time. We continuously look ahead to advance the future and technology of our industry, by rolling up our sleeves to solve tough problems together, and by learning from our successes, as well as our failures.
Being a software engineer at FactSet is to shape the future of investments technology. Our engineers use cutting edge technologies including machine learning, natural language processing, predictive analysis, and cloud computing to solve some of the investment community’s greatest challenges – relying every step of the way on some of our most creative minds to create sleek and intuitive UIs that make our products among the industry’s easiest to use.
We’re looking for hard-working and out-of-the-box thinkers from all software engineering disciplines to bring new perspective and fresh ideas to our team. Engineers are aligned with specific teams where they design and implement applications for integration within the FactSet product suite and deployment to investment professionals worldwide.
Our engineers find the right balance between FactSet's flexible environment where everyone can contribute individually, yet at the same time cultivate a community where they can depend on each other for help, learning, and development.
- Analyze data sets and protoype as many experiments as necessary to converge to the optimal practical solution
- Work with New York-based Alpha Pro machine learning team in order to expand the predictive modeling services, and work with state-of-the art stack of data modeling paradigms
- Get responsibility right from the first day and the unique chance to enrich the environment of key metrics Portware’s predictive services rely on
- Extract, transform, and load data
- Write reusable research code and prototypes for predictive models
- Take part in all aspects of the software life cycle, including specification, analysis, design, development, unit testing, product deployment and support
- Search, read, understand, and communicate relevant academic papers related to your projects
- Participate in brainstorming sessions for new ideas
- Pursuing a MSc/PhD in a quantitative field, such as Applied Mathematics, Computer Science, Engineering, Physics, Operations Research, Econometrics, Stochastic Finance.
- Excellent analytical skills
- Hands-on design and implementation of machine learning solutions
- Interest in the financial markets as well as previous experience in financial services
- Sounds knowledge and application of advanced statistical methods and time series analysis
- Proficiency with R, Python, and Matlab
- Strong computer science fundamentals (data structures & algorithms) and solid object-oriented design skills
- Excellent communication skills