Responsibilities

:

Architect and design groundbreaking machine learning techniques tailored to financial tasks within Knowledge Graphs, creating innovative solutions that extend beyond traditional applications.

Enhance and scale our AWS-based infrastructure to ensure the efficient, reliable delivery of ML and AI solutions, including the integration of LLM.

Work closely with data scientists and ML engineers to integrate and manage diverse ML and NLP models within production environments effectively. Offer expert advice on model selection and deployment strategies.

Manage the entire software development lifecycle, from the initial design and coding through to testing and the deployment of financial AI applications.

Construct and maintain robust data pipelines capable of processing complex structured and unstructured financial data, guaranteeing the highest quality inputs for our models.

Act as a mentor to team members, promoting a culture of innovation and continuous learning within the team.

Minimum Requirements:

3-5 years of profound software engineering experience, significantly focused on AI/ML solutions in production environments.

Skills:

Demonstrated expertise in cloud architecture (primarily AWS) and familiarity with a broad range of services.

Solid understanding of Natural Language Processing/Machine Learning/Deep Learning fundamentals and their real-world applications, evidenced by a successful history of model development and deployment.

Proficient in Python, with strong skills in Docker and API development.

Excellent communication abilities, capable of engaging both technical and business audiences alike, and leading cross-functional projects.

Knowledge of major database architectures including MongoDB, SQL, NoSQL, and Vector databases.

Additional/Desired Skills:

Experience with Knowledge Graphs and architecting LLM-powered solutions.

Deep familiarity with the financial data, its applications, and specific industry challenges.

Expertise in NLP libraries such as nltk and SpaCy and proficiency in unstructured text analysis.

Demonstrable leadership capabilities and experience in mentoring or leading a team.

Education:

An MS degree in Machine Learning, Computer Science, or a related field is preferred.

Key Technologies:

Python

Deep Learning Frameworks: Tensorflow, Keras, PyTorch

NLP/Chatbot Technologies

Cloud Platforms: AWS, Azure

Graph Technology: Neo4j

Why Join Us?

High-Impact Work: Your work will directly impact how financial professionals globally make pivotal decisions.

Collaborative, Innovative Team: Collaborate with top-tier engineers and scientists to advance the frontier of financial AI.

Focus on Growth: FactSet is dedicated to continuous learning and offers ample opportunities for professional development.

Join us to push the boundaries of financial analytics and technology, harnessing your skills to make a significant impact in the industry.