Data scientists are software developers with a knack for numerical analysis. When I differentiate my role as a data scientist from my role as a software developer, I am highlighting my skills with…
- Machine learning
- Matrix algebra
- Numerical optimization
- Statistical analysis
- Data visualization
- Scientific computing stacks (SciPy, Anaconda, etc.)
- Distributed computing tools (Spark, Hadoop, MRO, etc.)
Of course, I may use many different tools in any given data science task. My career has been defined by addressing numerical analysis needs with the right software to get the job done. In the simplest terms, programming is the best way to actuate a talent in mathematics.
When numerical analysis is the goal, some software development always is part of the solution.