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Data Scientist Tools

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Quick list of Tooling required by large companies, when sourcing a few job listings ( November 6 )

listed for my own personal use.

Blizzard:

• Database querying (e.g., SQL, HiveQL)
• Data visualization (e.g., R plotting, matplotlib, Tableau)

Amazon:

• Fluency in a scripting or computing language (e.g. Python, R, Java, C++, etc.)
• Experience with SQL and at least one scripting language (preferable Python)
• Proficiency in at least one statistical software package such as R, Stata, Matlab, or Python.

Google:

Experience with statistical software (e.g., R, Python, MATLAB, pandas) and database languages.
Applied experience with machine learning on large datasets.

Apple:

We seek proficiency with SQL. Experience with big data technologies such as Hadoop and Spark preferred.
Proficient with Python or R and data visualization tools such as Tableau for full-stack data analysis, insight synthesis and presentation.

Tesla:

• Proficiency in Python, SQL and experience with ML libraries and frameworks like Scikit-learn, h2o or Spark ML.
• Solve complex industrial and technical problems using advanced mathematical modeling and optimization techniques, including but not limited to, big data pre-processing, problem formulation, features engineering, algorithmic selection and evaluation, hyper-parameter tuning for machine learning, and deployment.

Microsoft

• Experience with data analysis and statistical tools (e.g. Python, R, SAS, Matlab or SPSS).

AirbNB

• R/Python; SQL/Hive
• Manipulating large-scale data sets
• Descriptive and predictive modeling

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