Texas, United States, Remote
September 14, 2022
Apply NowJob description
FactSet, a leading provider of financial information and analytics, helps the world’s best investment professionals outperform. The Company has been included in FORTUNE's 100 Best Companies to Work For and a Best Workplace in the United Kingdom and France. FactSet, with $1.4 billion in annual revenues, is headquartered in Norwalk, CT, employs over 9,600 people worldwide and has offices within North America, Europe and Asia Pacific. Since 1996, the Company has been publicly traded on the NYSE and NASDAQ under the symbol FDS.
The Machine Learning team at FactSet is made up of engineers and scientists who develop and implement scalable ML platforms and systems that enable us to delight our customers with new products and services. We combine cutting edge machine learning techniques with the company’s unique data assets to optimize all the business decisions we make. In this role, you will be part of our world-class machine learning team and advance the state-of-the-art in financial applications ranging from natural language processing, information retrieval, and predictive analytics. Our work spans the company’s lines of business, with exceptional opportunities in each.
The successful candidate will develop new machine learning methods tailored to financial applications such as intelligent searching of financial information and financial predictive analytics. Machine learning techniques will include supervised, unsupervised, deep learning, and other algorithms related to time series analysis. In addition to using and adapting existing models, you will be expected to develop new techniques especially suited to financial applications. The candidate will help in the identification and solution of new problem areas.
You’re an engineer who enjoys going deep into the technical details to build innovative products and solutions. You’re excited to join a team that delivers applications used by millions of people around the world. You have a sense of ownership, responsible for your work from end-to-end, and you have a knack from coming up with creative solutions to complex problems. If you’re keen to work on real-world challenges with some of the most talented applied engineers in the world, we’d love to hear from you.
Key Responsibilities:
Research and development of systems with natural language analysis, information retrieval, and financial predictive analytics.
Technology the team is currently using:
The Machine Learning team at FactSet is made up of engineers and scientists who develop and implement scalable ML platforms and systems that enable us to delight our customers with new products and services. We combine cutting edge machine learning techniques with the company’s unique data assets to optimize all the business decisions we make. In this role, you will be part of our world-class machine learning team and advance the state-of-the-art in financial applications ranging from natural language processing, information retrieval, and predictive analytics. Our work spans the company’s lines of business, with exceptional opportunities in each.
The successful candidate will develop new machine learning methods tailored to financial applications such as intelligent searching of financial information and financial predictive analytics. Machine learning techniques will include supervised, unsupervised, deep learning, and other algorithms related to time series analysis. In addition to using and adapting existing models, you will be expected to develop new techniques especially suited to financial applications. The candidate will help in the identification and solution of new problem areas.
You’re an engineer who enjoys going deep into the technical details to build innovative products and solutions. You’re excited to join a team that delivers applications used by millions of people around the world. You have a sense of ownership, responsible for your work from end-to-end, and you have a knack from coming up with creative solutions to complex problems. If you’re keen to work on real-world challenges with some of the most talented applied engineers in the world, we’d love to hear from you.
Key Responsibilities:
Research and development of systems with natural language analysis, information retrieval, and financial predictive analytics.
Technology the team is currently using:
- Python
- Deep Learning: (Tensorflow 2, Keras, PyTorch)
- Apache Spark
- NLP/Chatbot
- Cloud: (AWS, Azure)
- Solid foundation in Natural Language Processing/Machine Learning/Deep Learning/AI.
- MS degree in Machine Learning, Computer Science or a related discipline to come up with ideal solutions for challenging problems.
- Strong proficiency with Python programming.
- 3-5 years hands-on experience using Machine Learning/NLP frameworks to build, validate, test and deploy models.
- Write and design application services needed for other engineering teams to use our processes.
- Knowledge of Distributed Systems, Databases: SQL, NoSQL.
- Strong verbal and written communication skills.
- Relevant Industry experience.
- Familiarity with horizontally scalable environments (MapReduce, Hadoop, Spark) and in cloud (AWS).
- Familiarity with Deep Learning toolkits such as Torch, TensorFlow 2, Keras, PyTorch and others is desirable.
- Financial/Investment/Business knowledge.
