7 Steps to Landing Your Dream Job as a Data Scientist

I recently went through the process of a finding a new role as a data scientist, and I would like to help others in successfully navigating the process of landing their dream roles as data scientists with a few key tips..This article provides my advice in 7 steps.The below write up provides additional context about my 7 tips for landing your dream job as a Data Scientist:Tip 1: Find the role you want.Tip 2: Getting a job means dealing with rejection..Be PERSISTENT.Tip 3: Study Statistics, Machine Learning, SQL, and Python.Tip 4: If you want the job, go above and beyond.Tip 5: Study the company culture, people, and business models.Tip 6: Negotiate and leverage.Tip 7: Choose the role that fits best for YOU.Extra: Helpful Resources to Help You PrepareTip 1: Find the role you want.The title Data Scientist is used to mean different responsibilities for different companies, and sometimes the title means different responsibilities even within the same company..The Head of Data Science discusses their three roles of data scientists within AirBnB..Data Scientists at AirBnB work on either analytics, algorithms, or inference.Dan Frank (Data Scientist at Coinbase) discusses the roles of Data Scientists at AirBnBAt Lyft, they divide the roles of data scientists into two groups..The second set of data scientists are known internally as Data Scientists, which was a role for which I applied and interviewed.From my interactions with the this team of data scientists, they act very much as Product Data Scientists determining what metrics matter most in measuring the success of products, how to measure these metrics, how to improve existing products, and what new products to pursue.The other companies I interviewed at had smaller data science teams with less defined roles..At these companies, I asked what the exact problems they were hiring data scientists to solve..It was important to me that they had systems that were already in place to ensure that the endeavors of data scientists at these companies would be successful.For example, had they hired the engineering talent already to collect the data necessary to answer their questions of interest and build out data science products?Was there someone in leadership that created the right sort of hype associated with data science applications?Were there both realistic expectations of timelines for building out certain data science applications, as well as an understanding of how data science would be integrated into organizations around the company?Ask questions about how you (and other Data Scientists on your team) are expected to make an impact on the company goals.These questions allow the company to understand what you bring to the table, as well as allowing you to understand what their expectations are for you..Be PERSISTENT.Once you have completed the process of figuring out the types of roles you should apply for, you need to apply to these roles..Your goal as a candidate is not to berate the interview process of any company..Stay focused.It doesn’t matter how far into the interview process you make it; if a company does not believe you to be the right fit, thank them for their time and move on.The talk below is by Greg Kamardt, who now works as a Data Scientist at Salesforce..The screening process for most jobs follows a similar pattern.Initial phone interviewTechnical phone interviewTake home assessmentOnsite interviewFinal negotiations phone callIn the remainder of this section, I will dive into the details of each part of the interview pipeline..You are also informed about the steps of the interview process.It is useful at this stage to have a few questions ready about the role, as well as questions about the company.. More details

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