FactSet, a leading provider of financial information and analytics, helps the world’s best investment professionals outperform. We've been recognized as one of FORTUNE's 100 Best Companies to Work for and a Best Workplace in the United Kingdom and France. Headquartered in Norwalk, CT, with over 9,600 employees worldwide and offices across North America, Europe, and Asia Pacific, FactSet has achieved $1.4 billion in annual revenues.

The Opportunity:

Join our world-class Machine Learning team at FactSet and advance the state-of-the-art in financial applications. We develop and implement scalable ML platforms and systems that empower us to deliver exceptional new products and services to our clients. You'll be at the forefront of innovation, combining cutting-edge machine learning techniques with FactSet's unique data assets to optimize business decisions across the company. We're driving innovation in natural language processing, information retrieval, predictive analytics, and more.

What will you be doing?

Shape the Future of Financial AI: Develop new machine learning methods specifically tailored for intelligent searching of financial information and financial predictive analytics. Apply supervised, unsupervised, deep learning, and time series analysis techniques.

Innovate & Solve Real-World Challenges: Help identify new problem areas where AI/ML can provide transformative solutions. Adapt existing models and pioneer new techniques optimized for the financial domain.

Cloud, NLP, & LLM Integration: Play a pivotal role in designing, implementing, and maintaining robust AWS-based infrastructure for serving a range of ML and AI solutions, including Large Language Models (LLMs). Collaborate to integrate LLM capabilities across our products.

Software Engineering Excellence: Deliver clean, well-tested production-grade code. Build dashboards and visualizations for financial experts, ensuring seamless user experiences.

Data-Driven Transformation: Design and implement effective data pipelines for both structured and unstructured financial data. Ensure data collection, quality assessment, and control processes are world-class.

Minimum Requirements:

• 5+ years of hands-on software engineering experience in production environments.

Critical Skills:

• Proven expertise in cloud architecture (ideally AWS) and associated services.
• Solid foundation in Natural Language Processing/Machine Learning/Deep Learning/AI.
• High proficiency in Python, Docker, and API development.
• Ability to collaborate effectively and explain complex technical concepts clearly.

Highly Desirable/Additional Skills:

• Experience with LLMs (OpenAI, Llama, etc.) and integrating them into production systems.
• Deep learning libraries (Keras, PyTorch, TensorFlow)
• Understanding of financial data and applications.
• Familiarity with big data tools (Pyspark, Hive) and databases (MongoDB, SQL, NoSQL)
• NLP expertise (nltk, SpaCy), especially with unstructured data.

Education:

• MS degree in Machine Learning, Computer Science, or a related discipline.

Why Join Us?

• High-Impact Work: Your contributions will directly influence the way financial professionals around the world make critical decisions.
• Collaborative, Innovative Team: Work alongside top engineers and scientists to push the boundaries of financial AI.
• Focus on Growth: FactSet fosters continuous learning and provides opportunities for you to advance your skills.

Key Technologies:

• Python
• Deep Learning: (Tensorflow, Keras, PyTorch)
• Apache Spark
• NLP/Chatbot
• Cloud: (AWS, Azure)

At FactSet, we celebrate diversity of thought, experience, and perspective. We are committed to disrupting bias and a transparent hiring process.  All qualified applicants will be considered for employment regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. FactSet participates in E-Verify. 

FactSet is an Equal Opportunity Employer – M/F/Veteran/Disability/Sexual Orientation/Gender Identity