Microsoft Vs Google: What Is Best to Work for As a Data Scientist?

An analysis and comparison of the best two data analyst certifications available right now.

Microsoft has several units, each with its own data scientists because it is a massive organisation with over 100,000 workers (part of the Data & Applied Sciences discipline). Although the objectives and tasks are different, there are common occurrences that bring people together (e.g., there is an internal annual Machine Learning, Analytics & Data Science Conference, and my team organises a semi-annual conference called OneAnalyst).

What is it like to work for the Analysis & Experimentation team as a data scientist in Microsoft?

• The data scientists at Microsoft are exposed to a wide range of essential products, including Bing, Office, and Skype. They are oversubscribed and give our work the highest priority based on a number of criteria, including the anticipated long-term benefit to Microsoft.
• The data scientists must be able to communicate with a variety of groups and support them through this culture shift because their focus is on assisting teams in becoming more data-driven and evaluating ideas through controlled experiments (such as A/B testing). The fact that Satya Nadella and, earlier, Qi Lu are supporting this top-down approach is beneficial.
• The platform and tools are designed to be self-service, but the data scientists act as the centre of excellence for the most challenging and fascinating studies. They assist experimenters, for instance, in understanding underlying causes and parsing unexpected outcomes. With some trials having an impact of tens or hundreds of millions of dollars, data reliability and quality are given top priority.
• They offer tools to increase the productivity of data scientists and other disciplines, whether through debugging, data summarization, the capacity to swiftly integrate sources and generate reports, etc. Their data scientists act as beta testers and oversee the feature development of these products, which increases their productivity. The best tools automate tedious tasks so that data scientists may concentrate on complex issues.

Microsoft has several divisions. Data scientists come under the category of "Data and Applied Sciences," which also contains the Address Book titles "Applied Scientists" and "Machine Learning Scientists." Each employee at Microsoft is assigned a level, such as 62, which, together with a few other parameters like region, defines your wage range, bonus range, and stock range. The conventional titles are mapped from levels into stages (or bands). The range of levels for data and applied sciences is 59 to 70. For instance, levels 63 and 64 correspond to "Senior Data & Applied Scientist." Principal Data & Applied Scientist level 65–67 and Partner Data & Applied Scientist levels 68–70 correspond to. Partners who reach level 70 are eligible for the Distinguished Engineer designation. Three factors are taken into consideration when determining promotions: budgetary constraints, personnel effect, and business needs (such as a wider scope). Employee impact is given the highest importance in my role as general manager at Microsoft. Promotions are given to employees who have had a significant influence. They are located in another group if there isn't a business need in a particular group (which is uncommon). Budget restrictions compel one to prioritise (you can't promote half the team at once, for example), but they are rarely a barrier since there are exceptions if the person deserves to be promoted.

Which professional certification for data analysts is the best?

Everyone will disagree on the greatest data analyst certification, depending on who you ask. However, this inquiry finds that the finest professional data analyst certification is the Google Data Analytics Professional Certification based on the (attempted) most objective criteria and a general comparison of the curricula.

Why Google has the greatest professional data analyst certification:

The typical pay for Google data scientists varies considerably based on location, education level, and years of experience, and it also depends on whether an employee is eligible for stock grants or an annual bonus. Google's data science interns earn an average of $7,500 per month at the entry-level of the spectrum, plus benefits including housing assistance and health insurance for the duration of their internship. In addition to cash incentives and stock awards, data scientists with an in addition to cash incentives and stock awards, senior data scientists who have more than five years of experience and a master's degree or a Ph.D. in a relevant discipline, such as machine learning, may earn about $161,544. Undergraduate degrees in a relevant subject, such as computer science, statistics, or mathematics, and some work experience may expect to make roughly $142,147 annually.

• Google has made the audacious promise that graduates of their school would be able to get employment in data analytics even without any prior relevant expertise. By making such a big assertion, Google commits to this guarantee. By providing tools to help graduates through the whole job preparation process, such as a resume-building tool, practice interviews, professional networking events, and a consortium of firms that will recruit graduates of the program, Google is well-positioned to live up to this claim.
• This credential is offered by Google in R, a programming language with a famously steep learning curve. The process of learning this language will go more smoothly if you have instructors and a community to support you. Graduates may then learn Python on their own without much difficulty because it is a fairly simple language to learn. In this approach, learning the challenging material first is advantageous and helps you become a more versatile data analyst who can join any organisation.
• Google has made the decision to offer the chance for a capstone project at the end of the course. Due to the pressures on the teachers and the added work required by the course provider, the majority of MOOCs do not provide a capstone project. Graduates of this school who take advantage of this chance put themselves ahead of other job hopefuls by having tangible proof of their talents and capabilities to address real-world challenges.
• With a curriculum that covers the fundamentals of data analytics for a fraction of the cost of a comparable Bootcamp or Master's degree, Google has offered the greatest value for your money. Additionally, because Coursera is hosting their certification, more people from all walks of life may now access the certification because interested students can apply for financial help if necessary.

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