Data Science & Analytics Intern — Predictive Revenue

Toshiba Global Commerce Solutions; Durham (NC); On-site; USD 12,000 - 24,000; Full time

Job summary

Toshiba Global Commerce Solutions is offering a Spring 2027 internship at our Durham, NC HQ. You will develop predictive models, analyze Salesforce data, and build pipelines to forecast revenue and inform planning decisions.

The role emphasizes applied ML, data science fundamentals, and cross-functional collaboration with business teams. Ideal candidates are pursuing a degree in data science or analytics, with experience in Python/R and SQL, and a willingness to work on-site at least one day per

Qualifications

• Must be a current student pursuing a bachelor’s or master’s degree in a data-focused field.
• Strong experience building, validating, and refining predictive models.
• Experience with Salesforce or CRM data and pipeline history is a plus.
• Proficiency in Python or R and SQL; familiarity with data viz tools.
• Willingness to explore AI/ML approaches and communicate insights clearly.

Responsibilities

• Develop predictive models to improve revenue forecasting and pipeline visibility.
• Analyze Salesforce data to identify patterns in deal progression and revenue realization.
• Apply statistical techniques to segment opportunities and estimate revenue potential.
• Build clean data pipelines and document Salesforce data structures for repeatable analysis.
• Translate findings into actionable recommendations for business planning and decision-making.

Skills

Predictive modeling

AI/LLMs understanding

Data analysis

Statistical thinking

Education

Bachelor's or Master's in Data Science/related field

Tools

Python

R

SQL

Power BI

Tableau

Excel

Power Automate

Job description

Toshiba Global Commerce Solutions is offering a Spring 2027 internship at our Durham, NC HQ. You will develop predictive models, analyze Salesforce data, and build pipelines to forecast revenue and inform planning decisions.

The role emphasizes applied ML, data science fundamentals, and cross-functional collaboration with business teams. Ideal candidates are pursuing a degree in data science or analytics, with experience in Python/R and SQL, and a willingness to work on-site at least one day per