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Customer Data ML Intern

AvePoint · Arlington, VA, United States

onsiteinternshipmid level

About this role

Role Description 

We are seeking a Customer Data Machine Learning Intern to help enhance and evolve our opportunity health scoring model, a critical capability used to improve pipeline quality, win rates, and revenue outcomes. This role will focus on expanding feature engineering, improving model performance, and supporting experimentation using customer, sales, and product data within Microsoft Fabric. The intern will work closely with Data Science, Analytics, and RevOps partners to integrate additional signals and ensure outputs are actionable for sales stakeholders. This is a hands-on opportunity to apply machine learning in a real business context and contribute directly to revenue-driving insights. 

Key Responsibilities 

  • Review and analyze the existing opportunity health scoring model, including features, logic, and performance. 
  • Explore and integrate multiple data sources such as CRM, sales activity, product usage, and historical deal data. 
  • Design and develop new features to improve predictive accuracy (e.g., engagement trends, activity velocity, deal progression signals). 
  • Build and maintain feature engineering pipelines to support model development and experimentation. 
  • Train, test, and evaluate machine learning models and compare results against existing baselines. 
  • Optimize model performance through tuning and iteration using business-relevant metrics. 
  • Support integration of improved models into existing scoring and reporting pipelines. 
  • Validate outputs with Analytics, RevOps, and sales stakeholders. 
  • Document model logic, features, assumptions, and recommendations for future improvements. 

Qualifications 

Required / Preferred Background 

  • Currently pursuing a degree in Computer Science, Data Science, Machine Learning, Statistics, Engineering, Analytics, or a related field (rising sophomore through graduate level).
  • Strong interest in applied machine learning and predictive modeling.
  • 4 Days in Office - Arlington, VA

Technical Skills (academic or project-based experience acceptable) 

  • Experience with Python or similar languages used for data analysis and machine learning.
  • Familiarity with machine learning concepts, including feature engineering, model training, and evaluation metrics.
  • Exposure to SQL and structured datasets.
  • Experience or interest in Microsoft Fabric, Azure, or modern data platforms is a plus.

Core Competencies 

  • Strong analytical and problem-solving skills with attention to detail and data quality.
  • Ability to work with ambiguity and iterate in an experimental environment.
  • Clear communication skills and ability to explain technical concepts to non-technical stakeholders.
  • Curiosity, ownership mindset, and eagerness to learn applied machine learning in a business context.

Any personal data you share with us during the application process will be processed strictly in compliance with applicable data protection laws and our Privacy Notice.

About AvePoint

Securing the Future. AvePoint is a global leader in data management and data governance, and over 21,000 customers worldwide rely on our solutions to modernize the digital workplace across Microsoft, Google, Salesforce and other collaboration environments. AvePoint’s global channel partner program includes over 3,500 managed service providers, value added resellers and systems integrators, with our solutions available in more than 100 cloud marketplaces. To learn more, visit www.avepoint.com . At AvePoint, we are committed to investing in our people. Agility, passion and teamwork set us up to do our best work and foster a culture where you are empowered to craft your career, make an impact, and own (y)our future. Unleash the power of you! AvePoint is proud to employ talent from many different backgrounds, experiences, and identities. We believe that diversity and inclusion drives our success and is at the core of how we hire, communicate, and collaborate to deliver value and excellence. We are committed to fostering an environment where people can bring their whole selves to work and feel a sense of belonging, and we continue to work toward creating a workforce that represents t...

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