The Data Scientist’s Path to Analytic Leadership

The Data Scientist’s Path to Analytic Leadership


by Eric A. King, Senior ProTech Consultant and Instructor

If you're not working on goal-driven impact and value-focused results that are measurable, understandable, accountable, and adoptable by the organization – then all the best scientific justifications, technical prowess, and methodological expertise just won’t matter. The vast majority of analytic practitioners end up toiling over incremental accuracy metrics for a model that’s ultimately never adopted or put into action.

Ironically, most data scientists view strategic implementation and soft skills as theoretical fluff – at their own peril. There's nothing more pragmatic than ensuring proper leadership attitudes, culture, environment, resources, team structure and a host of other strategic qualifiers prior to ever touching software, algorithms, and data. This provides a low-risk/high-impact approach to identify and prioritize valid opportunities.

Data scientists typically take too much pride in being highly technical mechanics, toiling under the hood to optimize the engine.  But it's the skilled driver and racing team leader who assesses the condition of the road, understands the rules of the race, what it takes to win, coordinates the various roles of the team, and how to manage them in order to claim the trophy. While mechanics schools are churning out plenty of technically capable practitioners to meet demand, there are very, VERY few skilled drivers and leaders out there.

However, this presents a tremendous opportunity. The data scientists who obtain the leadership traits, business acumen, and soft skills to strategically implement successful plans will bring real value to their organization, advance their career and stand out in an overcrowded field of self-proclaimed data scientists.

Fortunately, ProTech Training has programs to develop value-focused analytic leaders who can build end-to-end analytic operations at the enterprise-level from a formal implementation framework. These are the data science gems who are in high-demand and very low supply. Check out “Advancing the Analytics-Driven Organization” and “The Predictive Analytics Organization – Comprehensive Experience,” which trains all roles on the analytic team to collaborate toward standing up a thriving internal analytics practice or modeling factory. There are two separate modules in the Comprehensive Experience course for those whose roles are limited strictly to project Design or model Development.

Published November 30, 2017