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Data Scientist at Amazon: Turning Data into Business Insights

Are you excited about using data to develop scientific and analytical solutions to solve business problems? Data Scientists at Amazon are the link between the business and technical sides of Amazon; they transform and model large-scale data sets, while providing valuable insights for stakeholders.

Amazon believes that scientific innovation is essential to remain the most customer-centric company in the world. They leverage big data to study how customers shop on amazon.com, what they search for, what they buy, their comments on the products, and even their return habits.

Amazon has found that data can be a powerful tool to understand and improve customer experience. It is important for Amazon data scientists, as well as people throughout the company, to use this insight to make decisions such as pricing adjustments or when rolling out new features.

Amazon has developed sophisticated algorithms to learn from large amounts of data to automatically act on millions of dollars worth of inventory every week and establish plans for tens of thousands of employees. As a Data Scientist, you will leverage your research skills across Amazon and our Supply Chain as well as collaborate with academic researchers, in addition to publishing papers.

Amazon is Hiring Data Scientist to Improve Customer Exerience

Data Scientists are tasked with solving analytical problems, developing new models and algorithms, and cutting-edge research. They solve problems on diverse sets of data from businesses to create sophisticated models. Amazon wants you for this position if you’re eager to dive into data from a variety of sources, possess the ability to multitask and communicate effectively between stakeholders.

You will be able to synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication, enabling you to answer specific business questions and innovate.

Is this you? If so, read on.

How You Will Contribute

  • Amazon’s Data Science team analyzes large datasets from different parts of the supply chain. They combine this data with their knowledge about customer experiences and business operations to make important decisions that will enhance customer experience.
  • Ambitious by improving upon existing machine learning methodologies, developing new sources of data, testing for improvements to current models and parameters, running computational experiments, and more.
  • Formalizing theoretical assumptions, identifying outliers, and suggesting fixes or solutions to the identified problem is an essential part of data science.
  • Data Scientists work with business executives and technical team members to communicate the findings of their research, as well as any recommendations or insights they may have.
  • Amazon Data Scientists use code to interact with data and develop statistical, machine learning models and algorithms in order to provide business insights for stakeholders.

Skills You Need

Master’s or PhD degree in a quantitative field such as Machine Learning, Data Science, Statistics, Applied Mathematics, Physics, Computer Science, or Economics.

To be considered for this role, you must have either a Master’s or PhD degree. But the degree needs to be very specific, rather than just any Master’s or PhD.

So, let us break it down and explain …

You will likely already know what Data Science, Physics, and Computer Science are but there are a few others worth going over.

Machine Learning is the branch of Artificial Intelligence that gives computers the ability to learn without being explicitly programmed.

It’s a data science technique that can be used on any type of data to find meaningful patterns, recognize objects and classify images.

Here are some popular Machine Learning Algorithms: Linear Regressions, Support Vector Machines (SVM), K-Nearest Neighbors, Bayesian Networks, Hidden Markov Models (HMM), and Genetic Programming or Evolutionary Computation(GP/EC).

Applied Mathematics is the application of mathematical study to a variety of other fields such as physics, chemistry, and engineering. Applied Mathematics also includes industrial mathematics which applies mathematical skills to solve practical problems in business, manufacturing, or industry.

Some popular areas where applied mathematics are used: optimization models for supply chains, quality control, and logistics; data modeling techniques for marketing research; digital signal processing methods between phone conversations with speech recognition software.

Statistics is the field that deals with collecting valid measurements within some kind of population using appropriate sampling (the numbers you collect have to be representative) and then making inferences about this population based on these samples.

In order words, statisticians will make an educated guess about the value of a particular population from data.

Amazon is very picky when it comes to hiring data scientists, so be sure your credentials match their standards.

Fluency in a scripting or computing language (e.g. Python, Scala, C++, Java, etc.)

In addition to getting a Master’s or PhD degree, you are required to code too. This includes languages such as Python or Scala, but also things like SQL, R, and SAS which are often used for data processing and analytics tasks.

Here’s a brief description of what each of these programming languages does:

  • C++ was developed under the encouragement of Bjarne Stroustrup who designed it with five primary goals in mind: efficiency, control, safety, object-oriented programming, and generic programming. It is a statically typed high-level language that supports procedural programming paradigms with data types such as a scalar type (char), arrays, records, and pointers. C++ also has the ability to handle multiple tasks at once through its support of threading models or multi-threaded applications.
  • Python is a scripting language that is popular for data scientists. It’s often used to automate repetitive tasks and as a glue language between other languages, like Python scripts connecting R with Hadoop.
  • Scala has an advanced type system so it can be easier to enforce the types of values involved in calculations or outputted by programs than some other scripting languages are capable of doing (such as Python).
  • R, also known as the R programming language, is used by data scientists to explore and analyze data sets. It can be used for statistical computing and graphics needs.
  • SAS (Statistical Analysis System) is a programming language for statistical computing that was developed in the 1960s and 1970s with strong ties to IBM’s mainframe computers of this era. SAS provides powerful analytical tools for business professionals. The package enables users to get insight into their data using interactive graphs, charts, and tables on any device connected to the internet whether desktop computer, laptop, tablet, or smartphone.

Expert Experience

Amazon expects candidates who pursue a career in this role to have relevant expertise from their previous experiences. Amazon expects that potential candidates have strong analytical skills and can make predictions based on customer behavior.

  • Have experience processing, filtering, and presenting large quantities (Millions to Billions of rows) of data from different product groups and business functions
  • You also need to have experience working with Machine Learning/Deep Learning for real-world problems
  • You have 2+ years of relevant working experience in an analytical role involving data extraction, analysis, statistical modeling, and communication
  • You have 2+ years of experience with data querying languages (e.g. SQL, Hadoop/Hive)

Nice To Have

Amazon also looks for candidates who are naturally curious and eager to solve problems with data and statistical modeling. The candidate has experience with ambiguity, prioritizing needs, and delivering results in a dynamic environment will make you an asset at Amazon.

  • Expertise in reinforcement learning and/or deep learning
  • Superior written and verbal communication skills with the ability to advocate technical solutions to scientists, engineering teams, and business audiences are necessary.
  • Qualified candidates will have a deep dive into quantitative knowledge. Excellent skills in machine learning, statistical analysis, and problem-solving are essential requirements to become an Amazon Data Scientist

If you have a degree in Data Science and experience with large data sets, this career could be for you.

Check out the job list on Amazon.

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