Pine Labs is one of the leading merchant platforms in India and Southeast Asia. The company offers financing and last-mile retail transaction technology, where it provides a merchant platform and builds software for PoS machines. Currently, it serves more than 70,000+ retailers across India, including major retail outlets like Burger King, McDonald’s, Pizza Hut, Big Bazaar, Croma, Reliance Digital, and Pantaloons, among others. 

Basking on data, Pine Labs has an immeasurable wealth of data amassed over the last 20+ years, which is one of the key sources of differentiation in the industry. With a rich appetite for actionable insights, Pine Labs’ data science team believes in answering questions that drive business goals. 

“For example, to improve retention, we identify what drives churn and how we measure long term value, identify bottlenecks in the conversion funnel, and make suggestions for optimisation using data,” revealed Karthik Sivakumar, AVP and Head of Data Products at Pine Labs. 

Further, he said they have three stages of analytical maturity – i.e., build analytical frameworks; experimentation and automated decision systems; and predictive models and prescriptive analysis (as shown below).

Pine Labs told Analytics India Magazine that it is expanding its team and is now looking to hire lead data scientists, data architects, lead ML engineers and others across various experience levels with flexible remote work options in Delhi-NCR, Mumbai and Bengaluru.

Team Structure 

Pine Labs has a team of eight data scientists and data engineers working across finance, marketing, operations, payments and lending. 

But, the question is, how are they structured? To this, Sivakumar said that data scientists or pods are embedded with business teams. These data scientists share the same overarching goal of the department and have key results measured against the same. “We progressively move up the data hierarchy and across the stages of analytical maturity,” said Sivakumar. 

Interview process 

Pine Labs said that it follows a standard technical hiring process as established by their HR. 

However, some of the key performance areas (KPAs) used to assess the data science candidates include: 

• Strong problem-solving skills with a focus on product development
• Experience using statistical computer languages (R, Python, SQL, etc.) to draw insights from large datasets 
• Knowledge of advanced statistical methods and concepts and the ability to apply them to business 
• A drive to learn and master new technologies and techniques 
• Ability to work across cloud-native and on-prem data systems 

Expectations 

Sivakumar said that they look at hiring well-rounded individuals who have an inherent love for numbers, technology and want to empower businesses leveraging the same. 

He said the four pillars of being an effective data scientist are as follows: (see the image below)

Skills required: 

• Technology capabilities: SQL/Hive, R/Python
• Visualisation software: Qlik, Tableau, PySpark/Scala 

In terms of tools, applications, and frameworks used at Pine Labs, the team said their data stack is built cloud-native. Therefore, experience with cloud-based data and ML architecture with exposure to the AWS framework is preferred. 

Do’s & Don’ts 

Sivakumar said that thinking more about team structure, role name and hierarchy rather than the impact they can make, not doing enough homework on the company, the industry, or the role for which they are being interviewed is a major turnoff at Pine Labs. 

He said that the data team at Pine Labs is nascent yet rapidly expanding, and we are solving the most interesting and challenging questions in the industry. “Come join us, let us together drive the fintech revolution in India and across the world,” added Sivakumar. 

Work Culture 

Pine Labs believes in five core values that empower its data science team. These include speed, integrity, diversity, experimentation, and simplicity.

“If you are a person who is driven by challenges, is ambitious, and is willing to take full ownership of a business category, then we invite you to be part of Pine Labs,” said Sivakumar. 

He said, “To us, culture is not a poster on walls. It is not a set of policies. It is our ethos. It is about using data to create value and enable intelligent decision-making.” 

Click here to apply for data science jobs at Pine Labs today.