Myntra, a brand synonymous with online fashion and lifestyle in the country, brings together technology and fashion to create the best experience for its partners as well as costumes. The company currently has partnered with over 5000+ leading fashion and lifestyle brands such as Nike, Adidas, Levis, Puma, Wrangler, and others. In addition, it serves over 27,000 pin codes across the country.
Myntra’s data science team – one of the largest data science teams in the country – is the mastermind behind everything that the company does today, including business value, as a large majority of their solutions are AB tested.
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The team delivers many data science solutions, which are deployed at various customer touchpoints every quarter. “The models create significant revenue and customer experience impact, alongside providing real-time, near-real-time, and offline solutions with varying latency requirements,” explained Hrishikesh Vidyadhar Ganu, head of data science at Myntra.
Currently, Myntra works on a broad range of technical areas and business problems. Some of them include:
- Large scale recommendation systems: Like in-session intent, explore-exploit algorithms diversity, deep personalisation, identifying fashion trends, etc.
- Virtual Try-On: 3D virtual try-on for garments and beauty and personal care.
- Supply chain optimisation: Large-scale optimisation problems around regional utilisation and shipping promise. “We also leverage computer vision extensively for cataloguing, inbound QC, garment measurements, etc.,” added Ganu.
- Pricing: Demand modelling, portfolio pricing optimisation, optimised coupon allocation, etc.
The data science team at Myntra told Analytics India Magazine that it is currently hiring people for various data science roles across experience levels.
Team Structure
Myntra’s data science team is structured around pods-one-pod for a specific problem or business area. For example, there are separate pods for homepage, search, SCM inbound, SCM outbound, etc. Each of these pods is led by a data science manager and consists of 3-4 scientists. Multiple data science managers report to the head of data science.
Expectations
Following are the skills or expectations from data science at Myntra:
Statistics
Machine learning
Mathematical modelling
Systems
- Ability to translate ideas quickly into models and thus add value to business metrics
- Capable of working well with the product, business, and engineering teams
Data Science Tools used at Myntra
ML modelling tools: Scikit, PyTorch, TensorFlow
Data Processing: Spark, MapR, Kafka
Model Deployment: Specific tools for deploying /optimising inference on GPUs, mobiles, etc.
Model QC: Myntra uses internal tools to monitor and alter failures like concept drift, incorrect features flowing to online models, etc.
KRAs & KPAs
Here are some of the key result areas (KRAs) and key performance areas (KPAs) for assessing data science candidates at Myntra, as highlighted by Ganu.
See Also
- Contributions that add business value to Myntra both in the short and long term
- Technical depth, mastery of ML concepts and innovative application of those concepts demonstrated while executing projects
- Contributions to the larger data science team in picking up foundational pieces and ability to work effectively with their partner teams
Work Culture
“Being a people-first organisation, we are committed to fostering an enabling and empowering work culture that helps employees to continuously learn and grow, do meaningful work, and create a positive impact in the ecosystem. Moreover, our inclusive policies provide fair and equal opportunities to all,” said Ganu.
Myntra believes that care and empathy are the guiding principles that shape its people’s practices and policies. For instance, to extend optimal support for the well-being of employees holistically, they have unlimited wellness leaves and family care and recharge leaves. In addition, they have no meetings on Wednesday and post 5 pm on Fridays to help employees be more focused and productive without any distractions.
One of the differentiators at Myntra is the deep integration of data science with business, product and engineering teams. “The level of collaboration I have seen at Myntra is beyond what I have experienced anywhere else in my career. This ensures that other teams take a data science-focused lens when looking at new problems, and it helps data science by being extremely relevant to the company’s metrics and goals,” said Ganu.
What can you expect from Myntra?
Myntra said that it follows an open work culture, where all ideas are respected, and decisions are made on the strength of logic. Further, the team said there is a strong focus on research and publications and taking projects from research to production.
Plus, the company offers excellent learning opportunities both from internal experts as well as opportunities for online course-based learning. It also offers access to massive internal data sources and a variety of data science problems. In a way, this makes Myntra an attractive destination for top data scientists. “We have one of the largest data science teams in the country,” said Ganu.
“If you are someone who wants to work on massive datasets on problems that create huge business impacts while increasing your ML depth along the way, we are the team for you,” concluded Ganu.
Click here to apply.
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Source: https://analyticsindiamag.com/data-science-hiring-process-at-myntra/
