Developing data science skills in-house: Real-world lessons

Organizations are looking inward to fill data science needs, developing the culture, courses and programs necessary to deepen data analytics expertise.

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Specific analytic development requirements are being integrated into software product lifecycles. “It is our intent for everyone in the company to have an introductory course in analytics,” Fralick says. “The overall impact of the data science efforts on the organization and our business/data strategy have congealed with higher data volumes, customer expectations, and data fusion — to enable our business to be data- and model-driven.”

Coursework and collaboration at Ibotta

Over the past two years, Ibotta, a developer of mobile shopping apps, has built up an analytics team from within the organization through formal and informal training.

The team has developed six-week long courses in SQL, Python and Spark as well as short introductory training sessions on topics such as Tips and Tricks for Effectively Communicating Analytical Results, Pros and Cons of Frequentist vs. Bayesian Statistics, and Building Neural Networks leveraging TensorFlow.

“In addition, we hold bi-weekly brainstorming sessions where team members discuss and ideate on a variety of analytics and data science topics, and how each could be leveraged throughout the company,” says Laura Spencer, vice president of data analytics and science.

The company also heavily focuses on collaborative projects between analysts with different skill sets to encourage sharing of skills, capabilities and constraints.

“For example, we recently conducted a retention deep-dive with experts in marketing analytics, machine learning, and user research to build [recommendations] for the business,” Spencer says. “We also have several initiatives to encourage our employees to continue learning externally and bringing new tools and methodologies back to the team.”

Ibotta hosts and attends various big data and data science meetings near its headquarters. “We also sponsor each data scientist to attend a conference of their choosing each year and in return, the individual provides training of their conference learnings back to the rest of the organization,” Spencer says.

Over the past couple of years Ibotta's analytics team has grown to about 45 individuals and includes skill sets such as data engineering, statistics, and machine learning.

Copyright © 2018 IDG Communications, Inc.

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