Co-Op, Data Scientist

Job Description:

As a Co-op Data Scientist at Fidelity Investments, you will work closely with senior data science leaders to develop and deploy innovative data-driven solutions that support multiple business functions. This role offers exposure to cutting-edge analytics, Generative AI, and emerging agentic AI solutions. You will collaborate with cross-functional teams to translate business challenges into actionable analytical projects, enhancing decision-making capabilities and delivering measurable business impact.

Primary Responsibilities:
• Assist in the design, development, and deployment of machine learning and data science 
solutions for business applications, including predictive modeling, natural language 
processing (NLP), and generative AI use cases.
• Support integration of AI/ML models into production systems under guidance from senior 
team members.
• Conduct exploratory data analysis (EDA) to identify patterns, trends, and insights from 
structured and unstructured datasets.
• Participate in the development of algorithms and provide feedback on design and 
performance improvements.
• Assist with validation, testing, and monitoring of deployed models to ensure performance 
and reliability.
• Collaborate on generative AI initiatives, including prompt engineering, fine-tuning, and 
evaluation of large language models.
• Contribute to agentic AI research efforts, exploring autonomous multi-step reasoning 
systems for business problem-solving.
• Prepare technical and non-technical documentation for analytical solutions and present 
findings to internal stakeholders.
• Follow data governance and compliance practices to ensure data integrity and ethical AI 
standards.
Education and Experience:
Currently pursuing or having recently completed a Bachelor’s or Master’s degree (or foreign 
equivalent) in Network Science, Analytics, Data Science, Advanced Computer Science, 
Computer Science, Engineering, Information Technology, Information Systems, 
Mathematics, or a closely related field. Coursework or project experience in machine 
learning, natural language processing, and generative AI is highly desirable.
Skills and Knowledge:
• Fundamental understanding of supervised and unsupervised machine learning algorithms (Regression, Decision Trees, Neural Networks, Clustering).
• Familiarity with NLP techniques including Named Entity Recognition, text classification, and embeddings, as well as generative AI methods (transformers, large language models).
• Basic experience with agentic AI workflows, including multi-step reasoning and autonomous task execution.
• Proficiency in Python and familiarity with key ML libraries (scikit-learn, TensorFlow, PyTorch) and data manipulation packages (Pandas, NumPy).
• Exposure to cloud-based machine learning platforms (AWS SageMaker, Google Cloud AI, or Azure ML) is a plus.
• Ability to preprocess, clean, and visualize data using standard data science tools.
• Strong analytical thinking, problem-solving abilities, and eagerness to learn in a collaborative environment.
 

Placement in the range will vary based on job responsibilities and scope, geographic location, candidate’s relevant experience, and other factors.

Note, the application window closes when the position is filled or unposted.

Most roles at Fidelity are Hybrid, requiring associates to work onsite every other week (all business days, M–F) in a Fidelity office. This does not apply to Remote or fully Onsite roles. Some roles may have unique onsite requirements. Please consult with your recruiter for the specific expectations for this position.

Please be advised that Fidelity’s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

Certifications:

Category: