Blackhawk Network (BHN), a global leader in the branded payments space, recently launched Indian Strategic Development Centre in Bengaluru and is aggressively looking to on-board data scientists and product engineers. We got in touch with Radhakrishna Venketeshwaran, Vice President – Head of Strategic Development Centre, Product & Engineering, BHN, to deep dive into the company’s hiring strategy and hiring process for data scientists.
With a focus on building a product line related to its core expertise in finance, the company is looking to develop a full-fledged and sustainable analytics team for their India Strategic Development Centre.
Knowledge & Skill Sets While Recruiting Data Scientists
To make it into the BHN data science team, prospective candidates should have deep data expertise in areas such as predictive modelling, statistical modelling, multivariate calculus and data wrangling. They should also know languages such as Python and R, along with expertise in data visualisation.
“Regardless of background, they should have sufficient experience and understanding of business challenges, creating some valuable and actionable insights from the data, as well as communicating their findings to the relevant teams. They should have a strong foundation in probabilistic theory, stochastic calculus, and overall statistics,” said Venketeshwaran.
He further added that candidates who have worked independently on original research have the upper hand during the recruitment process, especially for senior roles.
“We are particularly looking for seasoned professionals who possess the ability to operate independently. However, candidates should have a thorough understanding of the system, and by looking at our data problems, they should be able to guide us with a possible solution. Thereafter, we will provide them with the right engineering support to evolve those ideas and convert them into business solutions,” he explains.
The Interview Process
The hiring process for data scientists at Blackhawk comprises multiple rounds of technical interviews, starting with an exploratory discussion round where they assess the candidate’s interest and understanding in data science.
The second round is about assessing a candidate’s technical ability, where candidates are given several use cases, for which they are expected to present a complete solution. Venketeshwaran says that this round also helps them to assess their past work experience and their choice of approaches. “We also do discussion rounds with senior-level executives after that, who share more data science use cases that we currently have, to deep-dive into their thinking process,” he adds.
The next discussion is usually with the product director and senior director to align candidates interest with business requirements and assess their ability to relate to their business. This is followed by one more round with our HR head to assess behavioural skills as well as determine the candidate’s cultural fit with the organisation.
On the types of questions that are usually asked in the interview process, Venkateshwaran shares that they ask questions around two core focus areas — one relating to their understanding of probabilistic theory and the other related to Dense Forest Trees. Additionally, there are questions around regression models followed by an assignment.
BHN identifies candidates from various sourcing job portals, HR consultancies, internal databases, employee referrals, and more. They also participate in hiring events periodically. Candidates can apply on Blackhawk Network’s careers page, or they can directly apply on Blackhawk Network India’s LinkedIn page.
Growth Opportunities for Data Scientists
Apart from data accessibility, data scientists at Blackhawk are provided with access to their proprietary data which allows them to work with a vast pool of information. A data scientist at BHN is expected to work in areas such as:
- Risk and fraud detection mechanisms where the company invests in creating analytics and data science-driven solutions.
- The second area is the commerce business, where the company deploys analytics to provide a personalised experience to the partners and their customers.
- Finally, analytics infrastructure is used for gamification and personalisation purposes.
“As we work towards making data science and analytics, one of the core components, BHN provides an opportunity to build a career in data science while given access to sophisticated data. We are sitting on a gold mine of data which can be explored for generating actionable insights,” shares Venkateshwaran.
Wrapping Up
Talking about some of the typical hiring mistakes that companies make, Venkateshwaran shares that companies usually do not have templates and use cases ready to judge a candidate’s skills. It is essential to analyse how a candidate approaches the problem. “Hiring data scientists is a tedious job, therefore during the hiring interviews, companies must give data scientists real-time assignments that can help them assess their problem-solving and analytical skills,” he says.
Finally, advising professionals who want to venture into the data science domain, he says to hone their skills beyond analysing past data and adding pure insights into the data. Further, to stay relevant in the market, data analytics professionals must continuously upskill and reskill themselves. “Focusing and being up to date with prediction and forecasting models is essential to excel in this domain, especially in the card and overall finance business,” he said on a concluding note.
