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Data Science Hiring Process At Standard Chartered Bank


Data Science Hiring Process At Standard Chartered Bank

Srishti Deoras

Standard Chartered is a multinational banking and financial services company headquartered in London. Being India’s largest international bank with 100 branches in 43 cities, SCB has a strong data science team largely centralised with a CoE model aligned to business segments. We got in touch with Anshu Sharma Raja, Managing Director, Global Head – Retail Banking Technology & Head GBS T&I Centres at SCB to understand the hiring process of data scientists at Standard Chartered.

Skills Required

Apart from the relevant technical skills, a problem solving and probing mindset is a must in a data science candidate, Sharma said. Having an insight-driven mindset is extremely important, especially when the team is seeking commercial outcomes, she further added. “These skills are not always the easiest to determine, but it is always important to see beyond the obvious,” she said. 

Talking about educational qualification, Sharma said, barring a niche set of roles where a PhD might be needed, there is no hard and fast rule requirement for academic requirements. The bank instead focuses on having relevant training on the tools and techniques required for data science working. “Experience and the ability to connect the dots across technology and business is the most important requirement,” said Sharma.

Sharma said an ideal data science candidate at SCB should understand the business context and comprehend the ‘why’ and then find solutions via the ‘how’. “A lot of time, data scientists seem to chase complex solutions and algorithms and miss out on the business context and market sensitivity,” she added.

What weighs more, educational background or skills? “Skills, absolutely. The sharper they are with experience, the better,” said Sharma.

Interview Process

Explaining the interview process at SCB, Sharma said that hackathons are the preferred way to shortlist candidates apart from discussion-oriented interviews. The hiring at SCB depends not just on getting a successful outcome but also on ways of problem-solving.

Having said that, demand and supply is one of the significant challenges in data science recruitment. Further, a lot of candidates add data science in their skill set to puff up resumes. To find the right people for the right roles is quite a challenge and takes time. “Hiring for generic job descriptions, not setting boundaries and scope of work is a pitfall. While there will be some headroom for creative growth, a direction and sense of common purpose are needed,” she added. 

Standard Chartered currently has a range of open positions across data engineering, analytics, visualisation, and data governance roles. The candidates can apply for these positions through the bank’s career portal, LinkedIn, or directly connecting with the recruitment team.

See Also
How Beginners Can Get Real World Job Experience Of Data Science

Being A Data Scientist At SCB    

      

From sourcing and preparing the right data sets to analysing and assessing risk, liquidity and customer behaviour, a large multinational bank has many challenges to deal with, said Sharma. Typically, a data scientist at SCB delivers, builds and maintains data-driven solutions core to financial markets; develop data science solutions; working with technology, cross-border functional and business product owners, as well as other peer groups, to ensure buy-in on topics and issues.

SCB provides many opportunities for data scientists to grow in terms of upskilling and exposure.

Pro Tips

Sharma advises internalising the specific area of skills and interest for those looking to make a career in the data science domain. It is crucial to understand the different facets of data analytics. Problem-solving and knowing business context and domain is a must. “Don’t mistake tools for techniques. Don’t chase tools alone because they will not remain the same given the fast-paced nature of the field. The fundamentals will hold you in good stead,” she said. 

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