SAIC's AI Farm System: Developing Tomorrow's Talent

A strong supply of data scientists will support government's uptake of AI endeavors

Bryn Stark

SAIC's edge for attracting the next generation of data scientists stems from the missions we support and the wealth of opportunities available in data science at the company. As the government incorporates artificial intelligence and machine learning into more programs, we need a strong supply of data scientists.

Last summer, our team focused on developing subject matter experts (SMEs) in data science through an internship program. We plan to continue the internship program for college students and have started a data science development program where junior employees can contribute, grow, and advance through exposure to real data science projects and mentorships in our AI lab.

Bringing AI into the federal government is a mighty endeavor. We want team members who are ready to embrace that challenge and help lead the charge. To thrive, they need to be both creative and independent, in addition to being highly technical.

In the context of an internship, perhaps more important than a deep understanding of math, statistics, and programming is the ability to think critically and reason through problems to find creative and feasible solutions. The fundamental technical areas will be developed, as students progress through their college courses, and refined on the job, as they learn to apply those skills.

Interns and junior employees work on projects that matter to SAIC and our customers. Last summer, one group of interns in our AI lab developed a deep learning algorithm for automated analysis of satellite images. Another designed a computer program to serve as a proof of concept for adaptive training in military simulations and corporate e-learning. And another contributed to ongoing research and exploration to support a major AI project.

FURTHER READING: SAIC interns go on to full-time positions


Just like senior data scientists, interns are challenged to consider all variables of a given problem--customer objectives, time and resource constraints, technical feasibility, etc. They must then come up with many alternative methods to approach the problem, consult domain experts and other resources where necessary, select the best solution, and execute it.

Interns have both the freedom and responsibility to pursue their own ideas, with guidance and mentorship from team members throughout the process. We look for tenacious students who take initiative to move forward independently but don't hesitate to ask questions when necessary.

Through the internship and development programs, we foster an environment in which interns learn extensively about machine learning, AI, data science, and the supporting skills necessary to complete projects in the field while contributing meaningfully to the team and the company. We guide the growth of the next generation of data science SMEs, investing in young and talented individuals who are motivated by the missions SAIC supports and opportunity to innovate in AI.

MORE FROM BRYN STARK: Machine Learning Redefines Vital Mission Work

We foster an environment where interns learn about machine learning, AI, data science, and the supporting skills to succeed.

Posted by: Bryn Stark

AI Scientist

Bryn Stark is an applied mathematician and lead data scientist in the AI lab in SAIC's Solutions and Technology Group. She designs and develops analytics, machine learning, and artificial intelligence solutions to address problem sets across a variety of defense and intelligence missions. Bryn earned a BA in economics from the University of San Francisco and a MS in data science from GalvanizeU, a tech incubator in Silicon Valley.



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