Must Haves :
You have at least 6 months of professional data scienceexperience.
You are an expert in SQL,Python, and related Python libraries (pandas, numpy).
You have domain expertise in statistics, mathematics,and probability.
You can build and applystatistical models in python using machine learning libraries, suchas scikit-learn and statsmodels.
You have adeep understanding of statistical hypothesis testing andexperimental design, data visualization techniques and tools (i.
e.matplotlib, bokeh, etc), and manipulation of large data sets.
You can demonstrate and explain the function ofmachine learning algorithms such as regularized regression, naivebayes, decision trees, ensemble methods, KNN, K-means clustering,and neural networks.
You are the person yourcolleagues naturally gravitate to when they are trying to figuresomething out.
You are eager to shape theskills, minds, and trajectories of the newest generation of datascientists.
Nice to haves :
You have proficiency with NLP python libraries such asNLTK; Hadoop or Apache Spark; D3.js or R.
You are on top of industry trends in big data, machine learning,deep learning, and AI.
You have previousdata science or engineering teaching experience, through a course,workshop, team training, etc.