#9 The Ultimate Guide to Nailing Your Data Science Application - Pt. 1 - DODS
Episode 9 of the Diaries of a Data Scientist podcast, hosted by Jasmin and Kate, titled "#9 The Ultimate Guide to Nailing Your Data Science Application - Pt. 1 - DODS" was published on February 4, 2024 and runs 36 minutes.
February 4, 2024 ·36m · Diaries of a Data Scientist
Summary
🔍 Are you eager to land your dream job? Look no further! Join us as we unveil the essential steps every aspiring data scientist 𝑺𝑯𝑶𝑼𝑳𝑫 𝑻𝑨𝑲𝑬 𝑩𝑬𝑭𝑶𝑹𝑬 venturing into the job market. If you like our podcast, please consider leaving a review on Spotify, subscribe on YouTube, and leave a comment and/or 👍! This would help us a lot ♥️ In this episode, we delve into the ‼️essential steps aspiring data scientists must take before applying for 👔positions in the field. Drawing from personal experiences, mentoring sessions, and consultations, we've crafted a comprehensive guide to help you navigate the complexities of the data science landscape. In this episode, we'll delve deep into: ▪️ 𝐏𝐫𝐞𝐩𝐚𝐫𝐢𝐧𝐠 𝐟𝐨𝐫 𝐒𝐮𝐜𝐜𝐞𝐬𝐬: Discover what steps you need to take before even thinking about hitting that "apply" button. ▪️ 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡: Learn the essential strategies for crafting a standout application that catches the eye of recruiters. ▪️ 𝐂𝐡𝐨𝐨𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐑𝐢𝐠𝐡𝐭 𝐅𝐢𝐭: Explore the crucial factors to consider when selecting the perfect company for your career aspirations. Here's a sneak peek at what's in store (unpaid advertisement, personal recommendations): @Kaggle: https://www.kaggle.com @GitHub: https://github.com @Kununu: https://www.kununu.com @Glassdor: https://www.glassdoor.de/index.htm @Linkedin: https://www.linkedin.com ML algorithms discussed in the episode: Liner regression Ridge, Lasso, Elastic Net regression Logistic regression Decision tree Random forest SVD k-NN DBSCAN K-means Naive Bayes
Episode Description
๐ Are you eager to land your dream job? Look no further! Join us as we unveil the essential steps every aspiring data scientist ๐บ๐ฏ๐ถ๐ผ๐ณ๐ซ ๐ป๐จ๐ฒ๐ฌ ๐ฉ๐ฌ๐ญ๐ถ๐น๐ฌ venturing into the job market.
If you like our podcast, please consider leaving a review on Spotify, subscribe on YouTube, and leave a comment and/orย ๐! This would help us a lotย โฅ๏ธ
In this episode, we delve into theย โผ๏ธessential steps aspiring data scientists must take before applying forย ๐positions in the field. Drawing from personal experiences, mentoring sessions, and consultations, we've crafted a comprehensive guide to help you navigate the complexities of the data science landscape.
In this episode, we'll delve deep into:
โช๏ธย ๐๐ซ๐๐ฉ๐๐ซ๐ข๐ง๐ ๐๐จ๐ซ ๐๐ฎ๐๐๐๐ฌ๐ฌ: Discover what steps you need to take before even thinking about hitting that "apply" button.
โช๏ธย ๐๐ญ๐ซ๐๐ญ๐๐ ๐ข๐ ๐๐ฉ๐ฉ๐ซ๐จ๐๐๐ก: Learn the essential strategies for crafting a standout application that catches the eye of recruiters.ย
โช๏ธย ๐๐ก๐จ๐จ๐ฌ๐ข๐ง๐ ๐ญ๐ก๐ ๐๐ข๐ ๐ก๐ญ ๐ ๐ข๐ญ: Explore the crucial factors to consider when selecting the perfect company for your career aspirations.
Here's a sneak peek at what's in storeย (unpaid advertisement, personal recommendations):
@Kaggle:ย https://www.kaggle.com
@GitHub:ย https://github.com
@Kununu:ย https://www.kununu.com
@Glassdor:ย https://www.glassdoor.de/index.htm
@Linkedin:ย https://www.linkedin.com
ML algorithms discussed in the episode:
- Liner regression
- Ridge, Lasso, Elastic Net regression
- Logistic regression
- Decision tree
- Random forest
- SVD
- k-NN
- DBSCAN
- K-means
- Naive Bayes
Similar Episodes
Aug 13, 2025 ·50m
Jul 31, 2025 ·50m
Jul 23, 2025 ·36m
Apr 15, 2025 ·32m
Apr 4, 2025 ·33m