Data scientists examine which questions need answering and where to find the related data. They have business acumen and analytical skills as well as the ability to mine, clean, and present data. Businesses use data scientists to source, manage, and analyze large amounts of unstructured data. Results are then synthesized and communicated to key stakeholders to drive strategic decision-making in the organization.
Skills needed: Programming skills (SAS, R, Python), statistical and mathematical skills, storytelling and data visualization, Hadoop, SQL, machine learning
The first waves of data scientists were primarily from development personnel, computer scientists, and engineers. They were the ones who created machine learning models, that optimized the process and minimized the cost function. They would analyze unstructured data, create specific programs for each problem, and, due to limitations of the computational processing, do manual map / reduces. Fortunately that time is gone, most of these operations have been greatly facilitated by high-performance programs and packages, and currently most Data Scientist is spending more time on modeling and less on engineering.
Dinesh recommends the following next steps: