Capco is a global management and technology consulting firm dedicated to the financial services and energy industries. The company hires Capability Leads across countries to envision, strategise and plan data science capabilities in respective geography. We got in touch with Riddhi Sen, Principal Consultant and Data Science & Machine Learning Capability Lead at Capco, to understand their data science hiring process.
With a non-hierarchical team-structure across projects, team members are assigned based on subject matter expertise, technical fit and experience.
At Capco, candidates with good technical skills in Python, SQL & machine learning knowledge get preference. The candidates should also have strong communication skills and the ability to understand the business context.
“In terms of educational background, we typically look for a PhD/MSc in scientific disciplines such as Physics and Computer Science. However, individuals with more varied backgrounds are also considered if they have relevant experience,” said Sen. Having said that ultimately a candidate’s ability to demonstrate the required skills is the most critical aspect. “A strong educational background is a good way of showcasing this, but it is certainly not the only way,” said Sen.
On the ideal data science candidate at Capco, Sen said a candidate should have an MSc/PhD in a quantitative subject, previous experience in consultancy and financial services, and robust data science experience.
Finding data scientists with excellent communication skills and a strong understanding of data science and machine learning applications in financial services is a big challenge. “For more senior roles, strong commercial knowledge is also required,” said Sen.
The interview process for hiring data scientist involves several steps:
- First round: A call with HR to talk through CV and discuss motivations for applying to Capco.
- Second round: An interview to understand the technical experience, how would a candidate apply those technical skills in a business environment, and the cultural fit.
- Case study round: Case study question with a senior member of the team – candidate is given a scenario relating to a client problem and some datasets. They are then asked to talk through how they would approach the problem technically and how to communicate the insights back to the client.
- Partner interview stage: A session with a member of the local Partner team.
- A wrap-up call with HR (and hopefully an offer!)
Sen said Capco does not work with third-party recruitment agencies but instead through a combination of employee referrals, graduate programmes, PhD recruitment initiatives and third-party recruitment platforms, and direct applications from interested candidates. “Because of Capco’s extensive data & analytics practice, there is also an increasing focus internally on upskilling data analysts to become data scientists,” she added.
Currently, at Capco India, there are 100+ open positions for data science and related roles, including Data Engineers, Data Analysts, Data Visualisation experts, Data Ingestion experts and Data Policy Auditing specialists. All live roles globally are listed on the Careers section of the website.
Common Interview Questions
Sen listed some of the common interview questions asked during recruiting data scientists at Capco.
- Why financial services?
- What sort of challenges do you think Capco’s clients typically want to solve with machine learning?
- How do you communicate a technical solution to a non-technical client?
- How have you mentored or upskilled others in the past?
- Talk through an ML problem you have solved in the past?
- What is the difference between covariance and correlation?
- Can you explain the workings of an algorithm you are familiar with?
- Can you explain how a receiver operating characteristic (ROC) curve works?
- What is a confusion matrix?
- Can you describe the differences between overfitting and underfitting?
Being A Data Scientist At Capco
Being a data scientist at Capco can be highly rewarding as the company offers many opportunities for them to learn from others and acquire new skills. They get to work with data engineers, architects and business consultants on interesting, real-world client problems. It provides an opportunity to become experts at scoping and defining data science problems.
Typically, a data scientist at Capco is expected to perform the following tasks:
- Leveraging a client’s data and using data science and machine learning to solve client problems.
- Communicating results and next steps to clients.
- Helping to grow and develop Capco’s data science capability and credibility (through ML training and publishing thought leadership, for example).
- Build data science/machine learning assets within Capco and contribute to our Capco Digital Labs initiative.
- Mentoring less experienced data scientists.
Talking about one of the common mistakes companies make while hiring data scientists, Sen said companies often place them in roles where, for example, only a data analyst is required. This quickly demotivates the data scientist and erodes their skill sets. “At Capco, our Capability Leads are careful to only assign data scientists to roles where their skills are fully utilised and plan any hiring accordingly,” she said.
Sen advised developing soft skills for professionals who wish to build a career in the analytics and data science industry, which is essential as a candidate progresses in the career. The second important thing is to focus on honing skills to solve high-value business problems.