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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.


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


• 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.


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


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.


• 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.


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


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

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