Out of the 7 billion + individuals in world, round 30% are disadvantaged of imaginative and prescient correction. Meanwhile, half of Indians (530 million) want imaginative and prescient correction, however solely 170 million have them.
Lenskart was based with a imaginative and prescient to assist individuals see the attractive phrase by revolutionising the eyewear class in India and past. The ten-year-old firm now delivers 7 million + spectacles a 12 months in India and Singapore and plans to ship out over a billion glasses over the subsequent ten years.
“AI and Tech are the core of Lenskart’s DNA with key innovations in our 3D-Try on and omnichannel digital and store model. By scaling up our core data science team, we are looking forward to transforming our customer experience and business as we expand not only in India, but also across Singapore, the Middle East and the US,” Amit Chaudhary, co-founder, Lenskart, informed Analytics India Magazine.
Analytics and knowledge science are core to Lenskart’s enterprise throughout a number of elements: retail & retailer analytics, digital & e-commerce analytics, advertising analytics, provide chain analytics, customer support, and extra. Lenskart recently hired Saurabh Agrawal because the Head of Analytics & ML. Since his appointment, Saurabh has aggressively appeared to increase the info science workforce, roping in knowledge engineers, enterprise analysts, knowledge visualisation consultants and knowledge scientists to construct the analytics basis at Lenskart.
We acquired in contact with Saurabh to know how the info science workforce is structured, the hiring course of and extra.
“Lenskart being an omnichannel direct to consumer retail brand provides a unique ecosystem of a full spectrum of analytics use cases which very few companies in the world provide. This creates a unique challenge and opportunity for professionals to learn and contribute, at the same time solve a 2 billion+ problem,” he stated.
Data Science Team At Lenskart
The knowledge science workforce at Lenskart is centralised and allows all vital enterprise capabilities throughout manufacturing, retail, digital, advertising, gross sales, operations, customer support and HR. “While the DS team works centrally, we are deeply embedded with the functional teams and have a very strong say in the operational strategy,” stated Saurabh.
The knowledge science workforce at Lenskart solves key enterprise issues throughout numerous useful domains. Therefore, to be a part of the info science workforce, the candidate is predicted to work throughout constructing experience in 1-2 topic areas, perceive the area and purposes of analytics. “Our team members are involved in data science use cases from start to finish. It gives them a kick to see the analysis they do being implemented and derive business impact,” he stated.
“We see that more than 60% of our customers in-store is digitally influenced. Understanding customer preferences and needs are crucial for us. We have a big focus on unlocking omnichannel analytics which requires us to understand the complex online – offline customer journey and use multi touch attribution method for driving marketing effectiveness”, he stated.
Lenskart has a cloud-first tech method. The tech stack includes applied sciences corresponding to knowledge lake — constructed out of AWS, Power BI for visualization, Google Analytics and Clevertap for digital analytics. For knowledge science, it makes use of R & Python and some different automation frameworks. The knowledge science workforce at Lenskart are anticipated to work round these applied sciences.
Skill Sets Required
Saurabh stated their key focus whereas recruiting knowledge scientists is on foundational expertise, a robust studying mindset and aptitude. Lenskart appears for a robust enterprise understanding, math, statistics, pc science and programming expertise.
Soft expertise are essential too. “Since our team is required to work with cross-functional teams, there is an equal focus on collaboration skills and good communication, especially the ability to explain analytics in simple language,” he added.
The most essential factor Lenskart focuses on is the eagerness for remodeling buyer expertise and enterprise with knowledge and algorithms.
Lenskart appears for candidates with a background in pc science, engineering (B.tech & M.tech) and MBA from reputed schools. “Strong grit, learning and innovation mindset always get preference,” he stated.
“We believe in the philosophy that your number of years of experience matters less to us. Your performance matters more,” he stated.
Data science recruitment at Lenskart is a mixture of lateral hiring, brisker hiring and cross actions within the firm and different industries. Most of the sourcing occurs straight and from LinkedIn and job websites. “We had some of our best people who took a career move internally as well from tech and product teams,” he stated.
The knowledge science interview course of at Lenskart includes the next steps:
- Round 1 – Introduction and Technical Round
- Round 2 – Detailed technical spherical, case research/machine check.
- Round 3 – Leadership spherical
- Round 4 – HR
Lenskart has a broad vary of roles inside the knowledge science workforce and throughout the corporate. It offers staff alternatives to attempt totally different roles within the knowledge science workforce throughout tech, product and enterprise capabilities.
Saurabh stated one of many vital errors is hiring solely knowledge scientists when an efficient knowledge science workforce wants a workforce with full spectrum of roles. It is like enjoying an orchestra, you want all devices within the band and having them work in concord is vital to have fantastic music.
The workforce at Lenskart is been scaled up with sturdy concentrate on variety, not solely gender, however individuals with totally different area background unfold throughout NCR and Bangalore. “While analytics is a heavy logical proper mind work, we’re consciously focusing equally on left mind elements of visible design & empathy serving to us drive subsequent degree workforce effectiveness “.
Saurabh stated the final word purpose of analytics and knowledge science is to boost buyer expertise and resolve enterprise issues. However, many individuals assume studying Python is equal to studying analytics.
“The passion for solving problems using data and algorithms is the most important thing one needs to discover within,” he stated.
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