Commitment and culture called him back: Meet 84.51° boomerang employee Chad Stripling

Sometimes, the grass really is greener on one side. After working at 84.51° for about five years, Chad Stripling took some time away to explore developing his skills elsewhere. While those experiences were valuable to him, Chad says 84.51°’s culture and commitment to data science kept calling him back, and he returned to the company in February of this year. Today, as Director of Data Science for the Interaction Innovation team, he works to provide tools, consulting and science to CPG companies and other partners to drive ROI for their business. We asked Chad to highlight some of the reasons behind his return to 84.51°.

I was a Lead Data Scientist with dunnhumby/84.51° in the Customer Communication Department. My work included the development and execution of customer retention and category expansion communication programs. It also included the development of machine learning propensity models across the marketing team. I also interned with the company prior to joining full time, so my first stint with the company was about 5 years in total.

During my time away, I first managed a pricing team for another food grocer. Then I managed a team focused on personalization for a clothing retailer. I was gone about three and a half years.

Although I enjoyed those roles and developing my skills in other areas, there were two key areas I missed about 84.51°. First, the culture at 84.51° is very unique. Not only are employees extremely collaborative, but the passion and effort they have for continued learning and development spurs innovation and career advancement opportunities. Secondly, both Kroger and 84.51°’s investments in data, technology and science are unmatched in my experience. Having best-in-class tools, tech stacks and resources allows our employees to free up more time for science and innovation.

I’m now Director of Data Science for the Interaction Innovation team, which provides tools, consulting and science to our CPG, Media and various other partners to drive ROI for their business. One of our main products, 84.51° Collaborative Cloud, provides clients with the most granular and accurate customer data in the market, which is enhanced through the science packages and consulting our team provides to them.

I returned for both the role and the company. 84.51°’s commitment to data science as a strategic advantage, along with the work-life balance encouraged by the company, were reasons I was eager to return. I was also excited to return for the role. At my roles outside of 84.51°, I experienced firsthand some of the challenges of not having the data or technology you need to make the right decisions. Knowing this role was dedicated to providing 84.51°’s best-in-class data asset and sciences to solve those same frustrations for our clients was exciting to me.

From a tech stack perspective, when I started at the company SAS and SQL were the primary coding languages, along with a lot of our data being stored on prem. Over the years, it has evolved to utilize Python and cloud computing software, platforms and APIs such as Azure, Databricks and Spark. Our science sophistication has also developed over time. The machine learning techniques and advanced algorithms used to deliver relevant messaging to our customers and business recommendations to Kroger is unrecognizable from where it was when I started.

84.51° is the most transparent company I have ever been around. They are very open about sharing where their priorities are and providing feedback on how initiatives are performing. Second, they are dedicated to a work-life balance. Advocating for taking time off, allowing for remote work and investing in benefits makes you proud of your company and work. Lastly, their philosophy of technology being a key differentiator for the company allows employees to create efficiencies with BAU work and enables greater capacity for science and innovation.

It may sound cliché, but I would describe 84.51°’s culture as one of innovation and empowerment. The passion I see from employees to continually learn and develop is everywhere, from company-wide sharing sessions to small groups dedicated to learning a new machine learning technique. Similarly, I often see employees helping other teams solve problems and mentoring new coworkers. I also appreciate the empowerment to try new things. The ‘fail but fail fast’ mentality is fantastic. If an employee has an idea or recommendation, they are encouraged to go for it and if it fails that’s okay. Just keep striving for innovation and good things will come.

Yes, I think 84.51° does a great job with career development. This starts with the development program for entry-level talent. This program is extremely well structured and set up in a way to not only give new hires experience but to set them up with the skillset needed to be successful in any role. Similarly, the opt-in rotational program is a great way for employees to gain experience in new roles and positions. Lastly, having both technical and management track career advancement opportunities also allows data scientists to take their career where they want to.

My other employers were not as advanced from both a technological and data asset perspective. They were using tools that 84.51° has evolved from, and had to source data from other third parties. Utilizing third-party data had its own challenges, such as missing data from customers or having to rely on predicted data that breaks down in accuracy at more granular levels. There were also dramatically fewer data scientists at these companies compared to 84.51°, which made capacity and efficiency hard to manage.

Gain as much experience as you can. Look for opportunities to learn new areas that data science can be leveraged within your company or market. Network and learn from others to continue to develop your skillset. Lastly, do not be complacent in your coding skills. Data science is an everchanging landscape, so staying up to date on the most relevant coding languages and technologies will make you a more well-rounded data scientist and set you up for success in the future.