Data Science Hiring Process at CommerceIQ

With an AI team of 25 people, CommerceIQ has 5 open positions for data scientists.

Retail-tech unicorn, CommerceIQ, provides a cloud-based artificial intelligence (AI) platform for e-commerce companies to manage and optimise their advertising and sales across multiple marketplaces. The platform uses machine learning and automation to analyse data and provide recommendations for improving marketing, brand awareness, supply chain and sales operation, advertising campaigns and maximising sales. The company manages an array of consumer goods brands such as Colgate, Whirlpool, and Target, among others. 

Founded in 2019 by Guru Hariharan, CommerceIQ bagged a remarkable investment of $115 million during their Series D financing round in 2022, increasing the company’s overall value to a staggering $1 billion. 

CommerceIQ at series D valuation at Nasdaq

Analytics India Magazine got in touch with Prasun Kumar, senior VP of engineering and head of operations at CommerceIQ, to understand how the team leverages AI and analytics for their clients alongside their expansion plans. 

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CommerceIQ’s AI and Analytics Play

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With a data science team of nearly 25 people, CommerceIQ allots a specific team to work with each product line. 

Presently, it has five open positions in the following roles:

  • Principal Data Scientist: 12–15 years of experience
  • Junior Data Scientists: Zero to five years of experience

The company’s use cases include helping its customers understand the shoppers’ sentiment, or how its consumer brands estimate the market size, among several other cases of similar nature. The first step in solving problem statements is breaking them into different divisions such as prediction-based problems, categorisation-based problems, and NLP-based problems.

CommerceIQ uses Python and Google’s BERT in production but is also experimenting with GPT-3 for better results.

Interview Process

The ideal candidate for a junior-level data science position should have a strong foundation in data science models, basic mathematics and statistics, and probability. However, the most important attribute that the company seeks is curiosity and the ability to derive meaningful insights from data and translate them into compelling business solutions. 

Conversely, the company also values individuals with specialised skills, such as extensive expertise in natural language processing, predictive science, or time series, for a senior-level role. In addition, it is preferable if such candidates are well-versed in models like CART, Arima, neural translators, autoencoders, or deep learning models such as BERT and ChatGPT.

“We look for people who are good with NLP, time series, prediction-based data science modules, or those who are good with categorisation models depending upon the problems, and also depending upon the problems in the product lines that we are solving,” said Prasun Kumar.

The interview process for the AI team is multi-faceted, consisting of four to five stages. To begin with, CommerceIQ tests the candidate’s ability to work with data and think critically with the help of a case study. The second stage tests their understanding of data science models and their ability to choose the right approach. The next stage assesses problem-solving skills by presenting a business problem and evaluating the solution. The company also hires for cultural fit and also looks for leadership skills if the position is for a senior hire. 

The AI team’s success is measured by two key performance indicators (KPIs)—the degree of differentiation being driven through the product and the volume of intellectual property they generate.

Dos and Don’ts

Numerous candidates struggle to shift effectively between deep-diving into technical knowledge and communicating information with clarity to customers to drive engagement. Performance in data science requires both deep technical knowledge and effective communication skills. 

Kumar believes that it’s important for the candidates to be adaptable and shift gears between diverse problems. Additionally, it’s important to focus on fundamental principles, understand customer pain points, and acquire knowledge in relevant domains. 

Work Culture and Opportunity for Growth

“We are a very customer-obsessed company, so rather than looking at competitors, we’ll get to customers’ pain points, work backwards from customers and see what can be built”, added Kumar. 

Prospective employees hoping to join the company will have stability in the end-to-end product they are part of. They are given full ownership to make decisions for customers. 

The company has taken measures to improve work-life balance as well. For instance, the last Friday of every month is a designated holiday, which it calls “Wellness Recharge Day”; there are no meeting hours and so forth. 

Why Should You Join CommerceIQ?

CommerceIQ is focused on generating remarkable outcomes for its clients. Despite its desire for quick growth, it strives to improve the organisational work-life balance as much as possible and undertake endeavours that the team is truly passionate about.

Click here to join CommerceIQ’s team.

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