Data Science & Business Analytics Intern
At a glance
- Location
- Durham, NC
- Work type
- Onsite
- Visa sponsorship
- 2 H-1B filings by this company
- Category
- Data
Spring 2027 Data Science & Business Analytics Intern in Durham, NC. On-site internship at Toshiba Global Commerce Solutions HQ (Durham, NC); January 18 – April 23, 2027, 15-30 hours/week. Focus on predictive forecasting, pipeline analytics, modeling/segmentation, CRM data (Salesforce), applied ML/AI, and translating insights into business actions.
What they are looking for
Location: Durham, NC Department: 215110 - SGA Software Product Mgmt
Spring 2027 Internship: This position is located at our HQ in Durham, NC (Research Triangle Park). Expected program dates are January 18 – April 23, 2027. Anticipated working hours will be 15-30 per week. Final hours and schedule will be determined between the intern and their manager.
Note: Toshiba Global Commerce Solutions will not be providing visa sponsorship for this position now or in the future. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.
Introduction
Our Solutions Group analyzes the financial performance of our software product portfolio and the drivers of our P&L. We’re looking for an analytically strong, business-minded student to make our forecasting more predictive and more robust. You’ll work deeply with Salesforce pipeline data and build models that segment and score opportunities, forecast revenue, and surface the leading indicators behind forecast outcomes. You’ll also turn that work into insights that shape business planning.
What You’ll Work On
Predictive forecasting: Develop and enhance predictive models that improve revenue forecasting accuracy, strengthen pipeline visibility, and give forward-looking insight into revenue performance.
Pipeline analytics: Analyze Salesforce opportunity and pipeline data to find patterns in deal progression, stage conversion, win rates, deal velocity, and revenue realization.
Modeling and segmentation: Apply statistical analysis, clustering, regression, classification, and other techniques to segment opportunities, estimate their likelihood and revenue potential, and identify the key drivers of forecast outcomes.
Risk and leading indicators: Identify leading indicators, pipeline risks, and emerging trends to explain forecast variability and improve the reliability of revenue projections.
Data modeling and pipeline building: Explore and document Salesforce data structures, and build clean, well-modeled datasets and data pipelines to support repeatable analysis and modeling.
Portfolio and P&L context: Connect pipeline analytics to broader revenue expectations, software portfolio performance, and the drivers of the P&L.
Insight to action: Translate complex findings into clear, actionable recommendations for business planning and decision-making for both technical and non-technical stakeholders.
Applied ML and AI: Explore and prototype ways machine learning, LLMs, and AI agents can strengthen our analytics, such as extracting signal from opportunity notes and unstructured CRM fields or automating multi-step analytical workflows.
Continuous improvement: Build scalable, repeatable analytical processes, and monitor, backtest, and refine models over time to improve forecast reliability.
Required Qualifications
Must be able to work on-site at our Durham, NC headquarters at least one day per week; two days preferred.
Currently pursuing a bachelor’s or master’s degree in Data Science, Business Analytics, AI, Statistics, Computer Science, Mathematics, Economics, Business Administration, or a related field.
Strong experience building, validating, and refining predictive models (e.g., regression, classification, clustering, time-series forecasting) through work, internships, research, or substantial projects.
Strong understanding of AI/LLMs, including how they work, their limitations, and where they can be applied to analytics.
Experience working with Salesforce or other CRM data, including opportunities, stages, accounts, and pipeline history.
Proficiency in Python or R, including common data science libraries such as pandas and scikit-learn.
Strong SQL skills and comfort working with large, messy, real-world datasets.
Working knowledge of Excel and Microsoft Power Platform tools (e.g., Power Query, Power Automate) to analyze data and automate workflows.
Experience with data visualization tools such as Power BI or Tableau.
Excellent business judgment, strong analytical thinking, and attention to detail, with the ability to explain technical results clearly to non-technical audiences.
Curiosity, initiative, and a willingness to experiment with new technologies, take ownership of tasks, and learn through hands-on problem-solving.
Preferred Qualifications
Pursuing a master’s degree in a quantitative or analytics-focused program.
Coursework, internship, or project experience in finance, accounting, FP&A, or revenue/sales operations.
Basic understanding of P&L structure and how revenue drivers affect financial performance.
Experience with agentic AI, AI agents, and multi-step AI workflows.
Experience building AI-powered applications, automated workflows, or prototypes.
About the Company
Toshiba Global Commerce Solutions, Inc., is a dynamic billion-dollar global company based in Research Triangle Park, NC, providing retail store solutions to your favorite brands. Have you ever been in a hurry and made use of the self-checkout at Lowe’s Foods, earned fuel rewards at Kroger, or just paid for purchases at retailers such as Walmart, Michaels, Carrefour, The Gap, Calvin Klein, Boots, Cencosud, BJ’s, or Costco? These are just a few examples of our in-store solutions and impressive customer base that made us the world's installed market share leader.
The nature of retail is changing quickly, so if you share our 'Together Commerce' vision of a seamless two-way, participatory shopping experience, let’s get together to drive the new economy.
EEO
Toshiba is an equal opportunity/affirmative action employer that evaluates qualified applicants without regard to age, ancestry, color, religious creed, disability, marital status, medical condition, genetic information, military or veteran status, national origin, race, sex, gender, gender identity, gender expression and sexual orientation or any other protected factor. We also consider qualified applicants rega