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A data science portfolio people actually read

A folder of notebooks doesn't explain your thinking. FNJ's AI builder designs a data science portfolio where every project reads like a short analysis: the question, the data, the method, the charts and what it means, with links to the notebook and repo for anyone who wants the detail.

  • Next.js project
  • Static HTML
  • Push to GitHub
  • No FNJ runtime
Sample site with fictional names, made to show the kind of site the builder designs. Yours is designed from your description and the reference you choose.

The same sample at phone width. The builder designs every page at desktop, tablet and phone widths.

The sample, section by section

What a data scientist website needs

The sections the builder can design for you, and the job each one does. The starter prompt asks for these; add or drop any of them in your own words.

  1. 01

    Intro

    Your focus: analytics, ML, experimentation.

  2. 02

    Projects

    Question, method and headline result per card.

  3. 03

    Project write-ups

    Data, method, charts, conclusions, limitations.

  4. 04

    Tools

    Python, SQL, frameworks and platforms.

  5. 05

    Experience

    Roles and domains.

  6. 06

    Contact

    Email, GitHub, Kaggle and LinkedIn.

Made for data scientists, not for everyone

Starter prompt

A prompt written for data scientists

It opens in the builder ready to edit. Replace the words in brackets with your own details, change anything else you like, then add a reference.

Reference to add

A data journalist's or analyst's site whose charts and write-ups read well.

The builder takes a reference's look (layout, type, palette, spacing), never its words or images.

Build a data science portfolio for [your name], a [data scientist / analyst] focused on [forecasting / experimentation / NLP]. Open with a short introduction. Add a projects section with four projects (the question, the method and the headline result on each card) and a write-up page for each with sections for the data, method, charts, results and limitations, plus notebook and GitHub buttons. Add a tools section, an experience section and a contact section with email, GitHub, Kaggle and LinkedIn. Clean and analytical: a readable serif for body text, a neat sans-serif for headings, generous chart areas and a muted palette with one accent.

How it works

  1. 01

    Describe your data scientist site

    Open the builder with the starter prompt, fill in your details and add a screenshot or link of a site you'd like yours to look like. A reference is required: it's what makes the design yours rather than a template.

  2. 02

    Watch it design every page

    The builder plans the pages, palette and type, then builds each page section by section on a canvas at desktop, tablet and phone widths while you watch.

  3. 03

    Refine it, then take the code

    Ask for changes in plain words or edit by hand, upload your own screenshots, then download a Next.js project or static HTML, or push it to your GitHub, and host it where you like.

What it costs: From $25/month, or $29 once for 50 credits that never expire. No FNJ hosting fee: you host the exported site. See plans

Data scientists: questions

Can I embed Jupyter notebooks?
Not as live embeds. Export your charts as images for the write-up, and link a button to the notebook on GitHub, Kaggle or nbviewer.
Can I add interactive charts?
The builder places static images. Add interactive charts to the exported Next.js project with the library you prefer.
What goes into a data science portfolio project?
The question, the data, the method, the result and its limitations, with a link to the code. The starter prompt asks for exactly that structure.
Should I include my Kaggle work?
If it shows the kind of problem you want to work on, yes, as a project with a link to the competition notebook.

Related portfolio builders

Make your analysis readable

The builder opens with your data scientist prompt filled in. You edit it, add a reference, and watch the first version take shape.