Hybrid Data Science Intern: ML & Forecasting

GM Financial; Fort Worth (TX); Hybrid; USD 25,000 - 44,000; Full time

Benefits offered by this job

Networking opportunities

Independent and team project work

Career development

Executive and peer networking

Job summary

GM Financial, headquartered in Fort Worth, TX, invites a Data Science Intern to join a program focused on data-driven decision making, forecasting, and analytics. You will conduct research, analyze complex datasets and develop ML models to identify trends and improve operations, while preparing reports for stakeholders.

The role provides exposure to predictive modelling, analytics methodologies and practical business applications, with a hybrid work setup and opportunities for full-time

Qualifications

• Strong written and verbal communication required.
• Strong analytical, quantitative, problem solving, and conceptual skills.
• Detail oriented and able to prioritize tasks to meet deadlines.
• Able to work independently or in a team.

Responsibilities

• Modeling with forecasting, optimization, data mining and dataset analysis.
• Conduct descriptive and supervised ML studies with advanced techniques.
• Summarize, report and present findings to leadership.
• Analyze key metrics and perform data analysis.
• Develop algorithms or models to improve operations or answer business questions.
• Communicate insights and implications to senior leadership.

Skills

Communication

Analytical thinking

Problem solving

Detail oriented

Independent work

Education

Pursuing bachelor's or higher in CS/Data Science/Data Analytics/Info Systems/Statistics

Tools

Microsoft Copilot

Job description

GM Financial, headquartered in Fort Worth, TX, invites a Data Science Intern to join a program focused on data-driven decision making, forecasting, and analytics. You will conduct research, analyze complex datasets and develop ML models to identify trends and improve operations, while preparing reports for stakeholders.

The role provides exposure to predictive modelling, analytics methodologies and practical business applications, with a hybrid work setup and opportunities for full-time