Data Science Intern

Remote | Unpaid Internship | 6-12 months | 15–20 hrs/week | Master’s Degree Required

THIS IS NOT A SUMMER INTERNSHIP — WE ARE LOOKING FOR IMMEDIATE HIRES

About the Internship

• We are building a data-driven revenue intelligence system designed to transform how B2B leads are discovered, enriched, scored, and converted into sales opportunities.
• This internship focuses on using data science, predictive analytics, automation, and microservices to create intelligent sales pipelines that identify high-value companies and predict the services they are most likely to need.

• Unlike traditional engineering internships where interns simply implement predefined requirements, this role is highly strategic and research-driven. Interns collaborate directly with leadership to experiment with creative ways of using external data sources to improve lead discovery, enrichment, and predictability.
• You will research external datasets, build enrichment pipelines, design predictive lead scoring models, and develop modular components that become part of a scalable marketing and revenue intelligence infrastructure.

This role is ideal for Master’s students in Data Science or Data Analytics who want hands-on experience applying advanced data science techniques to real-world business problems like B2B lead generation, predictive targeting, and revenue intelligence systems.

What You’ll Work On

• • Research external B2B data sources, APIs, and datasets that can be used to discover and enrich potential client data.
• • Design and build data enrichment pipelines that collect additional information about companies and decision-makers from sources such as websites, LinkedIn, and third-party APIs.
• • Develop predictive lead scoring models that estimate which companies are most likely to need specific services.
• • Apply machine learning and statistical analysis to identify patterns that indicate high-value B2B opportunities.
• • Use semantic analysis and vector embeddings to match companies with relevant service offerings.
• • Build modular components and microservices that automate the lead enrichment and scoring process.
• • Create automation workflows that continuously collect, enrich, and evaluate lead data.
• • Design systems that predict which IT consulting or digital services a company may be interested in based on its data profile.
• • Build data-driven landing pages or dashboards that dynamically display insights generated from enriched datasets.
• • Integrate live data insights into landing pages used to book strategy calls for the sales team.
• • Experiment with different data acquisition strategies to determine which lead discovery methods produce the highest quality opportunities.
• • Document all systems, pipelines, and models so they can become reusable components within a scalable marketing infrastructure.

Technologies & Tools You May Work With

• • Python for data analysis, machine learning, and predictive modeling
• • SQL / PostgreSQL for data storage and querying
• • Vector databases such as Pinecone for semantic matching
• • APIs and third-party data providers for enrichment and lead discovery
• • Web scraping and automated data extraction
• • Automation frameworks such as n8n
• • Microservices architecture using Node.js / TypeScript
• • AI coding tools and modern AI-assisted development workflows
• • Semantic search and embedding-based data matching
• • Data visualization dashboards and dynamic landing page integrations

Types of Problems You May Solve

• • Predicting which companies are most likely to purchase specific services
• • Identifying hidden B2B opportunities through external datasets
• • Enriching incomplete company profiles with third-party data
• • Building models that recommend the most relevant data sources for different industries
• • Creating systems that automatically surface high-value leads to sales teams
• • Matching company characteristics with appropriate consulting or technology solutions

Who This Internship Is For

• This internship is ideal for graduate students who enjoy combining data science with strategy, automation, and product thinking.
• You may be a strong fit if you:

• • Are pursuing a Master’s degree in Data Science, Data Analytics, or a related field
• • Have experience using Python for data analysis or machine learning
• • Enjoy working with messy real-world datasets and extracting useful insights
• • Are comfortable researching APIs, data sources, and enrichment methods
• • Are curious about applying data science to sales intelligence and marketing systems
• • Enjoy building systems that automate decision-making and predictions
• • Are interested in combining data science, marketing, product strategy, and automation

Internship Details

• • Remote internship
• • 15–20 hours per week
• • Duration: 4–6 months
• • Unpaid internship designed for graduate-level learning and applied research experience
• • Work directly with leadership on experimental revenue intelligence systems
• • Opportunity to build portfolio-level projects involving predictive analytics and data pipelines