Data Science Intern - SaaS Customer Experience Analytics

Nasuni•Boston, MA

1d•Hybrid

About The Position

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 who is passionate about 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. Working closely with Customer Success leadership, Operations, and cross-functional teams, the intern will help transform customer data into intelligent insights that drive measurable business outcomes. This role offers exposure to modern AI techniques, customer analytics, and enterprise-scale SaaS data environments.

Requirements

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.

Nice To Haves

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).

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.