Beyond the job description: What 6 Chicago data teams really look for in candidates

Michael Hines

What data teams actually do varies from company to company. Job descriptions provide some insight into what a team does, but they don’t paint a complete picture, making it hard for candidates to know whether they’re the right person for the job. 

To cut through the confusion, we spoke with data teams at six Chicago tech companies about the skills and experience candidates need to stand out from the pack.

 

Grubhub's web and mobile food delivery platform connects people in over 1,000 cities with local restaurants. The company constantly analyzes its order data to improve the customer experience. Lead data engineer Ravi Nagubadi said a passion and knack for data along with a love for food and restaurants are a few of the things Grubhub looks for in prospective data team members.

What backgrounds do the members of your data team have?

Most studied computer science and information systems or mathematics and statistics. However, some also have backgrounds in economics, business and liberal arts. Some are serial startup and internet technologists, while others worked mostly at global corporations or big five consulting firms. What we all have in common is a passion for data and a knack for applying it to measure and advance the Grubhub story. We also all love food and restaurants!

What are the skills you look for in data team members?

Technical skills we look for include experience with data programming and manipulation using Python and advanced SQL; big data processing with Apache Spark or Hadoop; data warehousing; extract, transform and load processes; and data visualization with tools like Tableau. For some of our more advanced research and data science roles, we also look for experience with deep machine learning and modeling knowledge.

Above all, we value people who can dive into the guts of Grubhub's business and use data and toolkits to create and innovate in every area of the business.

What interesting projects is your team currently working on?

Grubhub is consistently collecting data to provide a better user experience for diners. In pairing diner data with restaurant and driver data, we’re able to continuously improve communication during the order experience. However, this is just the tip of the iceberg! We’re always hunting for more creative data minds to help us deliver further data innovation.

 

Uptake uses data from industrial IoT devices to provide predictive analytics to companies across eight different industries, including aviation, energy and rail. In recruiting new talent for its data team, data science lead Manny Bernabe said the company prefers candidates who have strong technical backgrounds and portfolios of work for review.

What backgrounds do the members of your data team have?

Several members of our team come straight from academia. We also have team members who worked at companies like Google and Facebook, as well as government agencies like NASA and the National Oceanic and Atmospheric Administration.

Our team’s background is about one-third computer science, one-third statistics and mathematics, and one-third hard sciences, including physics, biology and neuroscience. We aim to keep our mix close to equal parts of those three categories as it adds domain expertise across a range of specialities.

What skills do you look for in data team members?

We look for candidates with a strong background in computer science and programming. We also seek candidates with work we can review, whether that’s in published academic papers, code repositories like GitHub or data science competition platforms like Kaggle. We also prefer candidates who’ve contributed to open source data science software packages.

Combined, our team members have published over 80 academic papers. Five of our data scientists are adjunct professors at local universities, and we employ four of the top 1 percent of Kaggle competitors, including one who is ranked 13th.

What interesting projects is your team currently working on?

We work with data coming off of edge devices and moving assets like locomotives, airplanes and wind turbines. We’re working on contextual data sources like satellite imagery, industry-specific weather metrics and more. The volume and velocity of the data we work with is incredible, and provides a level of insight our customers can’t find elsewhere.

 

Evive uses big data and predictive analytics to improve employee benefits. The startup gathers all workplace benefits on a single platform and sends personalized real-time reminders to encourage employees to take advantage of benefits and perks. Data science director Arun Rajagopalan says his data team looks for candidates who can “tell the story” behind data.

What backgrounds do members of your data team have?

Our data science team is a multicultural group of academic researchers and software engineers. Researchers usually have a strong academic background in probability, statistics and machine learning. Engineers are responsible for building data pipelines and deploying data models in production. They usually have backgrounds in computer science and are curious about statistical techniques.

What skills do you look for in team members?

For researchers, we look for experience building data models and with deep dive analysis to help tell the story behind the data. Technical qualifications for engineers include R, Python, Java, SQL and experience with large-scale data systems. Spark or Flink is also a plus.

What interesting projects is your team currently working on?

We are building deep learning models that leverage health history and claims data to predict future health conditions, including diseases and medical procedures. We're also working on models that use doctor referral data to build graphical models for scoring. This is combined with pricing data to guide our doctor recommendation engine.

Through a unique combination of big data and the latest behavioral science, we’re redefining the experience of using benefits and achieving amazing results, for employers and employees alike.

 

Procured Health builds software that helps hospitals make evidenced-based purchasing decisions. The company’s platform combines financial and clinical data to identify which devices and drugs are most effective and cost-efficient. Associate director of data analytics Mike Doerner said the company seeks individuals from mixed backgrounds that bring new perspectives to problem solving when looking for new team members.

What backgrounds do the members of your data team have?

Our team has experience in different quantitative fields such as engineering and economics, and many have backgrounds in healthcare fields such as epidemiology, neuroscience and biology.

What skills do you look for in team members?

They should be passionate about finding insights using data and hungry to strengthen their technical skills through continuous learning. To test for these core competencies, we integrate a realistic data exercise and scenario-based questions into our hiring process.

What interesting projects is your team currently working on?

The data analytics team is working to properly classify messy data by linking medical devices and drugs to clinical evidence and providing key insights. To do this, we leverage machine learning, taking in new data sources and developing data analysis and visualizations that drive hospitals to action.

 

KAR builds a wide range of technology for wholesale buyers and sellers in the used car industry. VP of product and analytics John Manganaro and director of data science Tom Kozlowski said that while the KAR data team values technical skills, they also emphasize critical thinking and problem-solving abilities.

What backgrounds do the members of your data team have?

Manganaro: When forming the original data team, we made it a point to reach outside of the automotive industry to find fresh perspectives within a relatively stagnant industry. Some members of the team were once in academia, but most come from the world of business. It’s important to have a diversified group of individuals with different experiences that complement each other. 

What skills do you look for in data team members?

Kozlowski: We don’t have specific technical skills that need to be met as long as candidates can demonstrate knowledge of statistical and machine learning approaches as well as determining when various approaches would serve better to solve a specific problem. Overall, we prefer candidates who utilize open source data science tools and understand frameworks available for them to apply data science to business problems.

In our opinion, the most important skill is effective communication. Candidates are asked to present to a panel during the final interview stage. This lets us assess how efficiently and effectively candidates explain complex solutions and ideas to an audience with varying backgrounds.

What interesting projects is your team currently working on?

Kozlowski: Combining team members from product and data science into one group has created a culture that focuses on making data science outputs both valuable and useable. Taking incredibly complex models and translating their outputs into intuitive actions within software products is imperative for our success.

Our initiatives are always named “Super Secret Project _____ “ in order to stress the importance of being first to market with our work and holding off our competitors. Unfortunately, I am sworn to secrecy at this time…

 

Mattersight uses advanced analytics and data science to help brands have better phone conversations with customers. Its technology analyzes conversations in real time to match customers with support agents who share their personality traits. Vice president of behavioral and data science Andy Traba says the company seeks candidates with the ability to create data-driven products that produce a tangible business benefit.

What backgrounds do members of your data team have?

We like diversity. Some data team members come from academia while others have previous experience at SaaS companies. Analytical backgrounds are targeted, like statistics, economics and mathematics, but we have very successful people from a variety of backgrounds.

What skills do you look for in data team members?

Technically, we look for experience with SQL, R and Python. Anything else is an added bonus. The ability to create data-driven products that produce tangible business benefits is also really important. Given our culture, helping non-data teams and the organization scale is another priority. You should also be a nice person who likes to have fun!

What interesting projects is your team currently working on?

One cool project involves using personality and behavioral characteristics of customers to route their phone calls to the best agents to service, sell or retain them. We’re also using machine learning to discover all of the conversational topics people are talking about and how those change across business outcomes or seasons.

 

Photos via featured companies. Uptake photo via Angela Champion, Uptake. Responses have been edited for length and clarity.

What does your company look for in candidates? Send us an email or tweet us @BuiltInChicago

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