Programming Skills – knowledge of statistical programming languages like R, Python, and database query languages like SQL, Hive, Pig is desirable. Familiarity with Scala, Java, or C++ is an added advantage.
• Statistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven companies.
• Machine Learning – good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests.
• Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis of a lot of predictive performance or algorithm optimization techniques.
• Data Wrangling – proficiency in handling imperfections in data is an important aspect of a data scientist job description.
• Experience with Data Visualization Tools like matplotlib, ggplot, d3.js., Power BI, or Tableau that help to visually encode data
• Excellent Communication Skills – it is incredibly important to describe findings to a technical and non-technical audience.
