The field of data science has emerged as one of the highest-paying fields in the technology industry. The capability to extract actionable intelligence from massive amounts of data has emerged as a key competitive advantage for organizations across all industry.
At the heart of the practice is the skill to collect, process, and examine data to address business questions. The workflow requires a blend of coding expertise including statistical programming, statistical knowledge, and domain expertise.
Predictive modeling constitutes a significant element of modern the discipline. Supervised learning models like random forests enable analysts to create predictive models that can estimate future outcomes based on training examples.
Visual analytics is an often underestimated but crucial skill in data science. The ability to present nuanced results clearly to executive stakeholders is what distinguishes good professionals from outstanding practitioners.
Technologies of the modern data scientist continue evolving rapidly. Python libraries like NumPy have emerged as industry standards for data analysis. Serverless analytics tools are making it more practical to work with data at scale.