Co-Op, Data Scientist

Job Description:

Fidelity Investments, Data Science Co-Op Intern 

The Team 

The Artificial Intelligence Center of Excellence in Fidelity’s Workplace Investing division is a team of data scientists responsible for creating artificial intelligence and advanced analytics solutions to meet the needs of our customers and clients.  Here, we use data science to do such things as uncover customer needs for deeper personalization, provide impactful business insights, optimize customer service, and create new tools designed to improve associate efficiency. 

The Value You Deliver 

The Data Science Co-Op Intern will have an opportunity to work on projects that will have a direct impact to Fidelity’s business.  Working closely with a team of data scientists, they will support advanced analytics/data science/AI projects such as: 

• Develop predictive models to help identify prospective customers and recommend benefit solutions to existing customers. 

• Design and execute experiments to measure the impact of new tools, processes, and models on key business indicators of sales. 

• Investigate new data sources to evaluate their usefulness in predictive modeling projects; generate new data using techniques like adversarial networks and textual data extraction.  

• Apply natural language processing and knowledge graph to identify trends and relationships in textual data to enhance customer relationship management activities.  

• Use explainable artificial intelligence (XAI) and effective data visualization techniques to help associates understand model predictions and justify business decisions.  

• Partner with AI/ML engineers to design, implement, and automate complete end-to-end data science pipelines using cloud technologies.   

The Expertise You Have 

• We are seeking talent who is working on their Master’s or PhD in Data Science, Computer Science, Statistics, or Operations Research or related field to join us for a robust 26 week co-op internship.  

• A strong Python programmer with demonstrated proficiency in data extraction, data engineering, data analysis, machine learning, data modeling and pipeline automation.  

• Familiarity with AWS tools for data science model development and deployment.   

• Experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.  

• Knowledge of advanced natural language processing, generative models, kno