The-Almost-Astrophysicist
The speaker in the video discusses the five important aspects of being a data scientist, including the need for constant learning and the ability to communicate complex models to non-technical stakeholders. She notes that the pay for data analysts and scientists varies widely across different industries and job roles, with quant finance being the most lucrative. While entry-level salaries for data science roles can range from $70k to $130k, depending on location and the industry, switching jobs every two years can lead to a 50% increase in salary over time. The speaker also shares her personal salary growth and emphasizes the importance of being curious and willing to learn as essential traits for data scientists.
In this section, the speaker discusses the five biggest points she has realized about data science. The first of these is that data scientists come in many different roles, meaning each project can require a slightly different skillset. Data science projects can vary hugely, from data analysis to machine learning or experiment design. The second point she highlights is the need for constant learning, with new packages and projects always emerging. The speaker stresses the importance of learning from others and keeping up-to-date with industry developments. The third point she makes is the importance of the ability to communicate as a data scientist, to be able to explain complex models and their implications in a way that non-technical stakeholders understand.
In this section, the speaker discusses the importance of understanding the value of using data to drive business decisions and the significance of communication skills in data science. The speaker also highlights the disparity in pay between different industries and job roles for data analysts and data scientists, with quant finance being the most lucrative. Furthermore, the speaker notes that not having a computer science degree may not be a disadvantage for entry-level data scientist jobs and shares her personal experience of having a physics degree instead, but mentions that having a degree may be necessary to move up to senior data scientist or lead roles. The speaker also briefly discusses entry-level salary expectations for data scientists, which she believes is relatively high.
In this section, the speaker notes that entry-level salaries for data scientists could range from 70k to 90k in non-tech companies while tech companies in Silicon Valley could offer around 110k to 130k, rising to six figures even for entry-level positions. However, the salaries are also location-dependent and vary from one city to another. For a more analyst role, the salary range could be 15k lower than 70k to 90k. The speaker also shares her personal salary growth from 80k to 110k as entry-level data scientist in Florida to 120k to 150k at her current job, which she joined as a data scientist without seniority. She adds that switching jobs every two years could increase the salary by 50% over time and highlight the importance of being curious and eager to learn, which are essential skills for a data scientist.
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