Rachael Maltiel Swenson shines a light on the roles and skill set of the analyst to help you hire the analyst you need.
In the world of data and analytics, the myth of the unicorn analyst still exists – the analyst who can log the data and build a data warehouse, run the latest machine learning models, and translate it clearly into business recommendations with domain expertise. In reality, these tasks require very different skill sets, from engineering to statistics to domain expertise (and that’s before even considering the soft skills around influence, communication, partnership, and more). Data and analytics professionals tend to have particular skill sets that set them up for excellence in a certain area of the field. Recognizing this can set an individual up well to differentiate and claim their data strengths and a company up well to hire for the talent they need. The world of data has three particular skill sets that cover a wide array of roles – domain expertise, statistics (including machine learning and AI), and engineering.
A domain expert deeply understands the context of which they are providing analytics and data support, be it product, marketing, sales, operations, etc. They know how to connect the dots from insights to action and what to recommend from the findings.
A statistical expert has a deep understanding of models and methodology to apply advanced techniques to drawing sense and insights of large data sets. AI experts would be part of this group as well.
A data engineer has the expertise to turn pixels and clicks into datasets that an analyst can then interpret. They know best practices for efficient extraction and manipulation of the data.
Key points include:
- Analyst roles
- Analyst skill sets
- Differentiating analysts
Read the full article, Analytics Roles & Skill Sets, on ArcGrowthllc.com.