Programming Skills – knowledge of statistical programming languages like R, Python , and database query languages like SQL , Hive, Pig is desirable.
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 PowerBI and Tableau that help to visually encode data
Excellent Communication Skills – it is incredibly important to describe findings to a technical and non-technical audience.