├── LICENSE └── README.md /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2021 sithankanna 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # 🚀 The Ultimate Product Data Science Resources 2 | The Ultimate Product Data Science & Analytics Resource 3 | 4 | 5 | > 👉 _Looking to break into Product Data Science or want to make your next move? Sign up to the_ [The Product Data Science Newsletter](https://buttondown.email/product-data-science) _to find out more_. 6 | 7 | 8 | # Product Data Science Interviews 9 | 10 | ## Facebook Product Data Science 11 | 12 | ### Overview 13 | * [iGotAnOffer: Facebook data scientist interview: the only post you'll need to read](https://igotanoffer.com/blogs/tech/facebook-data-scientist-interview) 14 | * [JayFeng: The Facebook Data Scientist Interview](https://towardsdatascience.com/the-facebook-data-scientist-interview-38556739e872) 15 | * [PrepFully: Facebook Data Scientist](https://www.springboard.com/library/data-science/facebook-interview/) 16 | 17 | ### Product Sense 18 | * [The Ultimate Guide to Cracking Business Case Interviews for Data Scientists (Part 1)](https://towardsdatascience.com/the-ultimate-guide-to-cracking-business-case-interviews-for-data-scientists-part-1-cb768c37edf4) 19 | * [The Ultimate Guide to Cracking Business Case Interviews for Data Scientists (Part 2)](https://towardsdatascience.com/the-ultimate-guide-to-cracking-business-case-interviews-for-data-scientists-part-2-7bc38fbe635f) 20 | 21 | #### Video Series 22 | * [Product Case Interviews Dos And Don'ts | Produce Sense | Data Science Interviews 23 | ](https://www.youtube.com/watch?v=nPJKFWMiIC8&list=PLY1Fi4XflWStFs6tLQ3Gey2Aaq_U4-Xnc&index=3) 24 | 25 | ### SQL Round 26 | * [Facebook SQL Questions](https://www.interviewquery.com/blog-facebook-sql-questions) 27 | 28 | ### Probability & Quant Rounds 29 | * [40 Probability & Statistics Data Science Questions](https://www.nicksingh.com/posts/40-probability-statistics-data-science-interview-questions-asked-by-fang-wall-street) 30 | * [Cracking the Facebook Data Scientist Interview - Quantitative Round](https://medium.com/@deepen.h.panchal/cracking-the-facebook-data-scientist-interview-part-2-cd3a8337c4af) 31 | 32 | ## Defining Metrics 33 | * [How to crack product metric questions in PM interviews](https://igotanoffer.com/blogs/product-manager/product-metric-interview-questions#metricqs) 34 | * [Neil Patel: How to Calculate LTV](https://neilpatel.com/blog/how-to-calculate-lifetime-value/) 35 | * [The Net Promoter Score](https://productmanagerhq.com/pms-metrics-net-promoter-score/) 36 | * [Sequoia Series: Data-Informed Product Building](https://medium.com/sequoia-capital/data-informed-product-building-1e509a5c4112) 37 | 38 | ### Evaluating Recommender Systems 39 | * [ML Metrics for Recommendation Systems](https://medium.com/qloo/popular-evaluation-metrics-in-recommender-systems-explained-324ff2fb427d) 40 | * [Evaluating Recommendation Systems](https://medium.com/fnplus/evaluating-recommender-systems-with-python-code-ae0c370c90be) 41 | 42 | ## Root Cause Analysis 43 | * [ProductManagerHQ: Metric Change](https://productmanagerhq.com/product-manager-interview-analyze-a-metric-change/) 44 | 45 | ## Tradeoffs 46 | * [iGotAnOfferTradeOffs](https://igotanoffer.com/blogs/product-manager/prioritization-and-trade-off-interview-questions) 47 | * [Kano & RICE Frameworks](https://bootcamp.uxdesign.cc/answering-trade-off-in-pm-interviews-b3868bb1d482) 48 | 49 | ## A/B Testing 50 | * [Emma Ding: 7 A/B Testing Questions and Answers in Data Science Interviews](https://towardsdatascience.com/7-a-b-testing-questions-and-answers-in-data-science-interviews-eee6428a8b63) 51 | * [Candor: A/B Test Interview Questions Asked at FANG](https://candor.co/articles/interview-prep/interview-tips-ab-testing-and-experiment-design) 52 | 53 | 54 | ### Udacity A/B Testing Course by Google 55 | * [Udacity](https://www.udacity.com/course/ab-testing--ud257) 56 | * [Study Notes - Udacity A/B Testing](https://nancyyanyu.github.io/posts/17c5bb19/) 57 | 58 | 59 | ### Practicalities of A/B Testing 60 | 61 | * [Guidelines for stopping an A/B Test](https://ux.stackexchange.com/questions/113212/guidelines-for-stopping-an-a-b-or-mvt-test-early-due-to-negative-metrics) 62 | * [AaronDeFazio: How to do A/B testing with early stopping correctly](https://www.aarondefazio.com/tangentially/?p=83) 63 | * [Early stopping in A/B testing](https://bytepawn.com/early-stopping-in-ab-testing.html) 64 | * [The pitfalls of A/B testing in social networks](https://tech.okcupid.com/the-pitfalls-of-a-b-testing-in-social-networks-17d631d7b20d) 65 | 66 | 67 | ## Funnel Analysis 68 | * [Funnel Analysis Examples and Case Studies in 5 Industries](https://amplitude.com/blog/funnel-analysis-in-five-industries) 69 | 70 | ## Cohort Analysis 71 | * [Cohort Analysis Using Python For Beginners- A Hands-On Tutorial](https://www.analyticsvidhya.com/blog/2021/06/cohort-analysis-using-python-for-beginners-a-hands-on-tutorial/) 72 | 73 | 74 | ## SQL for Product Analysis 75 | * [StrataScratch](https://www.stratascratch.com/) 76 | * [Leetcode Databases](https://leetcode.com/problemset/database/) 77 | 78 | 79 | ### Company Specific Questions 80 | * [Google SQL Questions](https://www.interviewquery.com/blog-google-sql-interview-questions) 81 | * [Amazon SQL Questions](https://www.interviewquery.com/blog-amazon-sql-interview-questions) 82 | 83 | 84 | ## Question Banks 85 | * [42 Data Science Product Interview Questions](https://www.stratascratch.com/blog/42-data-science-product-interview-questions/) 86 | * [Facebook’s Data Science Interview Practice Problems](https://towardsdatascience.com/facebooks-data-science-interview-practice-problems-46c7263709bf) 87 | 88 | 89 | ## Product Design & Improvment 90 | * [iGotAnOffer Product Improvement Questions](https://igotanoffer.com/blogs/product-manager/product-improvement-questions) 91 | * [iGotAnOffer Product Design Questions](https://igotanoffer.com/blogs/product-manager/product-design-questions) 92 | * [How to answer Product Improvement Questions](https://www.mypminterview.com/p/how-to-answer-product-improvement-questions) 93 | --------------------------------------------------------------------------------