and/or Machine Learning Algorithms — Table of Contents Introduction Algorithm Model Summary References Introduction Why is this important to know the difference? As data scientists, we have a lot of jargon to communicate between even other data scientists, as well as stakeholders. Two of those jargon words are algorithm and model. Both, are often used incorrectly, as they can…

A look into quantile loss and when to use it — business use cases — Table of Contents Introduction Regression and Loss Functions When To Use Quantile and When Summary References Introduction As a data scientist who has learned a lot online, I have seen a lack of discussions around loss functions that aren’t MAE or RMSE. For this reason, I am going to give a quick summary of…

Analysis of ZipRecruiter data. Are these what you expect? — Table of Contents Introduction Top 10 and Analysis Summary References Introduction Not only is knowing salary variability across states interesting, but it can also be useful for those looking to start their first job in data science, for moving to a new state, and for understanding where they stand in their current state. Perhaps…

Analysis of ZipRecruiter top 10 cities for Data Science Salary — Table of Contents Introduction Top 10 and Analysis Summary References Introduction Understanding the salaries for different cities can not only be interesting to know, but also beneficial in determining where to live or for reference when looking for your next position in data science. It is also important to note that a higher salary…

Table of Contents Introduction Startup Advantages and Disadvantages 3. Corporation Advantages and Disadvantages 4. Summary 5. References Introduction Being a data scientist at a startup is very different from being a data scientist at a corporation, or, in other words, a well-established, large company. The choice is ultimately up to you regarding which type…

Glassdoor vs ZipRecruiter vs PayScale — Table of Contents Introduction Average (with some popular companies) City Breakdown Seniority Breakdown Summary References Introduction This article is intended for those who are curious about salary breakdowns in data science for the year 2022. This information can be useful to make decisions in your career, whether it be for your current position or…

As a Data Scientist, collaboration is key — Table of Contents Introduction Planning and Grooming Stakeholder Updates Retrospectives Summary References Introduction A lot of the articles I write, as well as what is out there in general, focus on a singular data scientist, so I wanted to focus on something different itself. That is — the data science team. But first, let's…

How you can use DevOp tools for your Data Science and Machine Learning Operations — Table of Contents Introduction Why? Postman Rancher Jenkins Summary References Introduction The position of a data scientist can vary considerably, whether it be from only focusing on algorithms in a Jupyter Notebook, or being a full-stack software engineer utilizing data science models. In school or in your early career, it can be expected that…

Aside from the obvious, what are the specifics? — Table of Contents Introduction Product Manager Collaboration Project Lifecycle Management Summary References Introduction There are a lot of obvious differences between junior and senior data scientists, as the titles imply, but what are some lesser-known differences? …