Software Engineer III - Python Data Engineer

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.     Your Team's Impact Join our dynamic Machine Learning and AI team, where we build innovative models and solutions that drive business transformation and unlock new opportunities. You’ll be at the forefront of AI-powered initiatives, collaborating closely with product teams to shape the future of data-driven insights. This position offers high visibility and the chance to directly influence key decisions across the organization. You will report to the Manager of AI. Working Mode: Hybrid (3 days mandatory Office) What You’II Do Ingest and analyse various data sources to drive innovation in content creation. Automate the acquisition, relevance scoring and storage of incoming sources. Develop processes for data mining, data concordance and data production. Explore and evaluate new data technologies to build a scalable, cloud oriented data platform. Optimize data retrieval, develop dashboards and other visualizations for financial experts. System & Pipeline Development Architect and implement scalable ML pipelines for training, validation, inference, and monitoring. Collaborate with data engineers to ensure high-quality data ingestion, feature engineering, and labeling workflows. Contribute to MLOps practices by building reproducible, testable, and maintainable model delivery frameworks. Assist in designing, developing, and implementing machine learning models for real-world applications.  Work on data collection, preprocessing, feature engineering, and model evaluation tasks.  Collaborate with cross-functional teams including Data Science, Software Engineering, and Product.  Perform exploratory data analysis (EDA) and prepare datasets for training/testing.  Contribute to the deployment and monitoring of models in production environments.  Write clean, efficient, and well-documented code in Python or similar languages.  Stay updated with the latest developments in AI/ML research and tools.  Assist in model optimization, hyperparameter tuning, and performance scaling.  Stay current with the latest industry trends and technologies, contributing innovative ideas to ongoing projects.  Test and validate models to ensure their reliability and effectiveness in production environments.  Work with large datasets to extract meaningful insights using various statistical and ML techniques. What We’re Looking For …