Data Science Intern – SaaS Customer Experience Analytics

Austin Community College; Boston (MA); On-site; USD 27,552 - 41,328; Full time

Benefits offered by this job

Structured onboarding and mentorship

Hands-on project ownership

Collaborative office environment

Job summary

A technology company is seeking a Data Science Summer Intern for a hands-on internship focused on applying machine learning and AI to enhance customer experiences. The intern will analyze data, develop predictive models, and communicate insights to business leaders. Candidates should be pursuing a Master’s degree in a related field and have a strong foundation in machine learning, Python, and SQL. The internship is hybrid, allowing for three days a week onsite in Boston.

Qualifications

• Currently enrolled in a Master’s program in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.
• Strong foundation in machine learning, predictive modeling, and statistical analysis.
• Proficiency in Python with experience using libraries such as pandas, NumPy, and scikit-learn.

Responsibilities

• Develop predictive models to identify customer health risks and expansion opportunities.
• Analyze customer product usage and support data to find indicators of customer risk or growth potential.
• Design and test AI-driven frameworks for proactive customer health management.

Skills

Machine learning

Predictive modeling

Statistical analysis

Python

SQL

Education

Master’s program in Data Science or related field

Tools

pandas

NumPy

scikit-learn

Tableau

Job description

Data Science Intern – Customer Experience (AI & Proactive Customer Health and Insights)

Location: Boston Seaport or Marlborough, MA (Hybrid – 3 days/week onsite)

Duration: June 1, 2026 – August 7, 2026 (10 weeks)

Nasuni is seeking a Data Science Summer Intern to join our Customer Experience (CX) organization. This role is designed for a Master’s-level student with a passion for applying artificial intelligence and machine learning to real-world business challenges within a SaaS environment.

This is a highly hands‑on internship focused on building real solutions rather than passive research. The intern will analyze complex customer datasets, develop predictive models, and help design proactive frameworks that improve customer health, retention, and expansion opportunities.

Key Responsibilities

• Develop predictive models to identify customer health risks, churn likelihood, and expansion opportunities.
• Analyze customer product usage, engagement metrics, and support data to identify early indicators of customer risk or growth potential.
• Design and test AI-driven frameworks for proactive customer health management.
• Build and refine customer health scoring methodologies using statistical analysis and machine learning techniques.
• Explore NLP and large language model (LLM) applications to extract insights from unstructured data sources such as support cases, internal notes, and customer communications.
• Conduct exploratory data analysis to uncover behavioral trends, usage patterns, and drivers of customer success.
• Create visualizations, dashboards, and reports that communicate findings clearly to business leaders and CX stakeholders.
• Present insights, models, and actionable recommendations to the Customer Experience organization at the conclusion of the internship.

Required Qualifications

• Currently enrolled in a Master’s program in Data Science, Computer Science, Statistics, Applied Mathematics, or a related quantitative field.
• Strong foundation in machine learning, predictive modeling, and statistical analysis.
• Proficiency in Python with experience using libraries such as pandas, NumPy, and scikit-learn.
• Working knowledge of SQL for querying, transforming, and analyzing structured datasets.
• Ability to communicate complex analytical insights clearly and work effectively in a fast-paced, collaborative environment.

Additional Qualifications

• Experience with customer analytics, churn modeling, or customer health scoring frameworks.
• Exposure to NLP, LLMs, or generative AI applications.
• Familiarity with BI or visualization tools such as Tableau, and experience working with cloud environments (AWS preferred).

Benefits

• Structured onboarding and mentorship
• Hands‑on project ownership
• Exposure to enterprise marketing and communications programs
• A collaborative Boston Seaport office environment

Nasuni is an equal opportunity employer. The equal employment opportunity policy at Nasuni protects employees and job applicants from discrimination on the bases of race, religion, color, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, family medical history or genetic information, political affiliation, military service, or other non‑merit based factors. These protections extend to all management practices and decisions, including recruitment and hiring practices, appraisal systems, promotions, and training and career development programs.