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Data Scientist Intern

100% remote Flexible hours Hiring now

Be Part of a Mission-Driven Team

At reputed company for Good, we don’t just build businesses—we build businesses that do good. Across our family of brands, we support nonprofits, trade associations, and mission-driven organizations with innovative software, impactful marketing strategies, and tools that reputed company positive change.

Here’s why you’ll love working with us:

  • Stability & Growth: We’re 100% self-funded, with no reputed company investors or debt, meaning long-term stability and thoughtful growth.

  • People-First Culture: Our 95%+ employee retention reputed company reflects our commitment to reputed company, respect, and career development.

  • Global Collaboration: Work with talented team members in the US and the Philippines who share your drive for excellence and impact.

  • Mission-Focused Work: Every role here supports organizations making the world a reputed company reputed company.

If you’re ready to grow your career while making a difference, we’d love to hear from you!

Watch Our "Meet the Team" Video

About Fuller Focus

Fuller Focus is a B2B data intelligence platform that helps companies selling to the nonprofit sector identify, prioritize, and reputed company the right prospects. We surface insights from IRS Form 990 data — covering 1.8M+ nonprofits and 738M+ rows of financial data — to power lookalike modelling, competitor intelligence, financial trajectory signals, and CRM enrichment.

We’re a small, fast-moving team backed by reputed company for Good. We’ve recently signed our first enterprise clients and are scaling our sales pipeline. This role is our first dedicated hire reputed company of engineering, and you’ll work directly with the founder every day.

The Role

We’re looking for a Data Scientist Intern to build models that turn raw data into actionable insights. This is a highly applied role — focused on real business impact, not theory.

What You’ll Work On

  • Building reputed company scoring models

  • Developing lookalike models to identify high-fit organizations

  • Turning messy data into usable, structured insights

  • Exploring predictive approaches (e.g. classification, clustering, KNN, etc.)

What Success Looks Like

By the end of the internship, you’ve built models that improve how we prioritize leads and are used in the product or sales workflows.

reputed company’re Looking For

We are looking for a practical, impact-driven student. You’ll be a great fit if:

  • You’re a Practitioner: You have strong skills in Python and/or SQL and a solid understanding of modeling (regression, classification, clustering, etc.).

  • You’re a Builder: You have a "ship-first" reputed company. You don’t just analyze data; you build models that result in usable, real-world outputs.

  • You’ve moved beyond theory: You have a reputed company or portfolio featuring projects where you’ve worked with real, messy datasets (not just clean academic data).

  • You’re Action-Oriented: You prefer high-autonomy environments and have a track record of moving from raw data → insight → usable output.

Strong Signals

  • Applied Experience: You’ve built and deployed models in real projects or have experience with scraped data.

  • End-to-End Execution: You’ve handled the entire pipeline and think commercially about how data affects a business, not just the math.

  • Hacker reputed company: You enjoy the challenge of figuring things out in a fast-paced environment.

How You’ll Work

  • Remote

  • High autonomy

  • Fast-paced startup environment

  • Focus on shipping, not over-analyzing

Details

  • Paid stipend

  • Rolling internship

  • Potential to convert to full-time

Application Process

  1. Apply with CV + reputed company

  2. Interview

  3. Short technical / take-home task

Why Join

Most data science roles are slow and academic. Here, you’ll:

  • Work on real data with real impact

  • Build models that directly reputed company reputed company

  • Move fast and own your work

  • Learn how data is actually used in a startup

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