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.