Brag Doc Template
Data Scientist Brag Doc
A brag doc for a Data Scientist is the connection between your work and the decisions it moved. The trap is listing notebooks and models without showing the downstream business outcome. This template forces every analysis or model back to the call it influenced and the change that resulted.
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Data Scientist Brag Doc
What to include
DSs are graded on insight delivered, models shipped, and influence — did the work actually change what the company did? Each section maps to one. Fill 3-5 bullets per section. Tie every analysis to a downstream decision, every model to its deployment outcome, every memo to who acted on it.
Personalize
Optional · Appears in downloadThe template
Analyses That Changed Decisions
Investigations that surfaced an insight strong enough to move a call. Not the dashboard you built — what changed because of it.
- ·Which analysis surfaced an insight the team didn't have before? What changed?
- ·What recommendation did you make that leadership adopted?
- ·Which 'we should have done X differently' did you author from past data?
- ·What did you proactively investigate (not requested) that paid off?
- (no entries)
Models Shipped
Production models you built, deployed, monitored, or substantially improved.
- ·Which model did you ship into production? What does it predict, with what accuracy?
- ·How did the model's deployment change a business outcome?
- ·Which existing model did you improve (precision, recall, latency, fairness)?
- ·What model did you decommission or replace, and why?
- (no entries)
Data Infrastructure & Tooling
Pipelines, features, internal tools — the substrate you built that other analysts and DSs now use.
- ·Which pipeline, feature store entry, or shared dataset did you create or own?
- ·What internal tool or notebook template did you build that others use?
- ·Which data-quality issue did you find and fix?
- ·What did you automate that used to require manual analyst time?
- (no entries)
Stakeholder Influence
How you partnered with PM, Eng, Design, Exec — the alignment that turned analyses into action.
- ·Which exec briefing or QBR contribution did you author?
- ·Whose decision-making did you change by changing what data they saw?
- ·What disagreement between business and modeling did you mediate?
- ·Which trusted-advisor relationship did you build?
- (no entries)
Research & Methodology
Technical rigor — experiments, methodology improvements, internal or external publications.
- ·Which A/B or causal study did you design? What was the conclusive finding?
- ·What methodology improvement did you introduce (sequential testing, CUPED, etc.)?
- ·Which internal paper, post, or talk did you produce?
- ·What conference talk, blog post, or open-source contribution did you make?
- (no entries)
Mentorship & Team Contribution
How you raised the bar around you — onboarding, review, code quality.
- ·Which DS did you mentor or onboard?
- ·What review or pair-analysis did you do that changed someone's approach?
- ·Which guide or doc did you author for the team?
- ·What hiring loop or rubric did you improve?
- (no entries)
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Generated via Bloom — a career journal for iPhone. Bloom writes this document for you from your daily entries; the template is the manual version. bloomjournal.cc
Weak vs. strong bullets
The format does the easy part. The bullets carry the weight. A few examples to set the bar.
Weak
Built a churn prediction model.
Strong
Shipped churn prediction model into production: 0.78 AUC on holdout, replaced rule-based model with 0.61. Outputs scored 200K accounts weekly; CS retention team uses scores to prioritize at-risk outreach. Net retention up 2.3 points in the segment over Q3.
Weak
Did an analysis on user behavior.
Strong
Ran cohort analysis on 3 years of users to identify the activation predictors. Surfaced that month-2 onboarding completion is the strongest single predictor of 12-month retention (R² 0.71). Onboarding redesign followed in Q3; retained-cohort churn dropped 1.8 points.
Weak
Worked on data pipelines.
Strong
Built the unified feature store for the recommendation team's 12 models. Cut average model-iteration time from 5 days to 1 (consolidated 4 redundant pipelines). Now used by 3 adjacent teams.
Weak
Influenced product decisions.
Strong
Authored the pricing-elasticity memo that led to the v2 pricing decision. Modeled 3 scenarios across 4 segments, recommended option B. Leadership adopted; revenue per visitor up 22% in the 90 days post-rollout.
Manual template vs. Bloom generated report
Manual brag doc
- Works when you already remember the right examples.
- Requires manual sorting, rewriting, and evidence cleanup.
- Best for a one-time draft or printable structure.
Bloom generated report
- Starts from the work you captured when it happened.
- Organizes entries by goals, skills, impact, and review period.
- Turns daily evidence into shareable summaries and PDF reports.
You don't fill out a Bloom report. Bloom writes it.
The template above is the manual version. Bloom is the generated version. Thirty seconds when something good happens — speak it or type it — and at review time the entire document is in your share sheet. Same shape as the template. Your numbers, your names, your dates. Already written.
Get Bloom for iPhoneFree to start · iPhone · iOS 17+
Build the evidence before you need the template
Templates help with format. A career journal helps with memory. Use these pages together: learn the structure, generate a quick outline, then keep the source material current in Bloom.
Frequently asked questions
Can I use this as a Data Scientist brag doc app replacement?▾
You can use the template manually, but it will only stay useful if you update it consistently. Bloom is the app version: capture wins daily, then generate reports when you need them.
What should a brag doc include?▾
A strong brag doc includes dated wins, measurable impact, collaborators, skills, feedback, decisions, evidence links, and review-category alignment.
Is Bloom a brag doc app?▾
Yes. Bloom is a brag doc app and career journal that keeps the source material current, then turns entries into performance reports, recaps, and reusable career stories.