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
Educational Background: Bachelor’s or master’s degree in computer science, Engineering, or a related field is required.
Experience: 3-5 years of experience in software development, with a focus on systems handling large-scale data operations.
Strong foundation in Machine Learning; AI and Agentic Development concepts (supervised/unsupervised learning, regression, classification, clustering, etc.).
Good programming skills in Python (or similar languages like R, Java, C++).
Hands-on experience with ML libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch, Keras).
Understanding of data structures, algorithms, and basic mathematics/statistics and database management systems.
Excellent verbal and written communication skills, capable of articulating complex concepts to technical and non-technical audiences.
Familiarity with data handling tools (e.g., Pandas, NumPy, SQL).
Good analytical, problem-solving, and communication skills.
Ability to learn new technologies quickly and work independently or as part of a team.
Ability to work collaboratively in a team environment, contributing to group success while expanding personal skills.
Desired Skills
Strong experience and proficiency with Python, Pandas, Numpy and AWS APIs
Experience with modern data platforms such as Spark, Hadoop or other map/reduce big data systems and services
Experience with a variety of data stores such as ArangoDB, MongoDB, Cassandra, HBase, DynamoDB
Experience with AWS environment e.g., Amazon Kinesis, AWS Glue, Redshift, EC2, S3, EMR
Exposure to deep learning, NLP, computer vision, or reinforcement learning projects (academic or internships).
Knowledge of cloud platforms like AWS, Azure, or GCP.
Familiarity with version control systems (e.g., Git).
Understanding of MLOps concepts and pipelines (bonus)
What's In It For You
At FactSet, our people are our greatest asset, and our culture is our biggest competitive advantage. Being a FactSetter means:
The opportunity to join an S&P 500 company with over 45 years of sustainable growth powered by the entrepreneurial spirit of a start-up.
Support for your total well-being. This includes health, life, and disability insurance, as well as retirement savings plans and a discounted employee stock purchase program, plus paid time off for holidays, family leave, and company-wide wellness days.
Flexible work accommodations. We value work/life harmony and offer our employees a range of accommodations to help them achieve success both at work and in their personal lives.
A global community dedicated to volunteerism and sustainability, where collaboration is always encouraged, and individuality drives solutions.
Career progression planning with dedicated time each month for learning and development.
Business Resource Groups open to all employees that serve as a catalyst for connection, growth, and belonging.
Learn more about our benefits here.
Salary is just one component of our compensation package and is based on several factors including but not limited to education, work experience, and certifications.
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 www.factset.com 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.
