Software Engineer 3

FactSet creates flexible, open data and software solutions for over 200,000 investment professionals worldwide, providing instant access to financial data and analytics that investors use to make crucial decisions.

At FactSet, our values are the foundation of everything we do. They express how we act and operate, serve as a compass in our decision-making, and play a big role in how we treat each other, our clients, and our communities. We believe that the best ideas can come from anyone, anywhere, at any time, and that curiosity is the key to anticipating our clients' needs and exceeding their expectations.

We're seeking a passionate and experienced Senior Python & Machine Learning Engineer to join our Data domain team. You'll work on unique, one-of-a-kind problem statements using advanced GenAI, large language models (LLMs), and modern data engineering frameworks. You will help conceptualize and deliver impactful solutions that push the boundaries of data science and machine learning in finance.

Responsibilities

• Design, develop, and deploy sophisticated machine learning and GenAI models to solve complex data problems at scale.
• Implement, optimize, and scale ML solutions using Databricks, Spark, and cloud-native data ecosystems (AWS/Azure/GCP).
• Collaborate with other engineers, product managers, and UX teams to build robust, high-performance Python-based analytics pipelines.
• Develop and finetune LLMs and generative AI applications for structured and unstructured financial data.
• Architect data processing workflows leveraging Delta Lake, Feature Stores, and MLOps best practices.
• Translate cutting-edge research (papers, new ML techniques) into production solutions.
• Mentor junior data scientists and engineers on ML, best practices and GenAI.
• Work on one-of-a-kind data challenges, including entity disambiguation, real-time risk analytics, NLP, graph data modeling, and anomaly detection.
• Keep up-to-date with the latest in ML tooling, GenAI, Databricks, and cloud data infrastructure.

Requirements

• Bachelor's/Master's in Computer Science, Data Science, Mathematics, or related field.
• 5-6 years professional experience in ML, Python programming, and data engineering.
• Deep expertise in Python (NumPy, Pandas, PySpark, FastAPI, etc.) and ML frameworks (TensorFlow, PyTorch, Transformers).
• Practical experience with GenAI: training/fine-tuning LLMs (OpenAI, HuggingFace, Google Gemini, etc.), prompt engineering, and retrieval-augmented generation (RAG).
• Hands-on experience with Databricks (Workspace, MLflow, Delta Lake, Notebooks).
• Strong knowledge of cloud data platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Applied experience with ETL/ELT, data lakes, real-time streaming (Kafka, Spark Streaming).
• Proven track record of tackling cutting-edge data problems at scale – published research or open source contributions a plus.
• Familiarity with modern MLOps toolchains (MLflow, Airflow, Feature Store, CI/CD).
• Effective communicator with excellent collaboration skills.

Tech Stack

• Python, PySpark, FastAPI, Flask
• TensorFlow, PyTorch, HuggingFace Transformers
• Databricks, Delta Lake, MLflow
• AWS/Azure/GCP – S3, Blob Storage, EC2, Lambda, Step Functions
• SQL, NoSQL

Company Overview
FactSet (NYSE:FDS | NASDAQ:FDS) helps the financial community to see more, think bigger, and work better. Our digital platform and enterprise solutions deliver financial data, analytics, and open technology to more than 8,200 global clients, including over 200,000 individual users. Clients across the buy-side and sell-side, as well as wealth managers, private equity firms, and corporations, achieve more every day with our comprehensive and connected content, flexible next-generation workflow solutions, and client-centric specialized support. As a member of the S&P 500, we are committed to sustainable growth and have been recognized among the Best Places to Work in 2023 by Glassdoor as a Glassdoor Employees' Choice Award winner. Learn more at  and follow us on X and LinkedIn.

At FactSet, we celebrate difference of thought, experience, and perspective. Qualified applicants will be considered for employment without regard to characteristics protected by law.