Creating cutting-edge data pipelines for seamless, real-time inventory-content integration with brands and stores. Currently focused on generating automated product attributes using Machine Learning models.
Team Vision is comprised of individuals with a diverse set of skill set and focus areas. Broadly the team has a pool of engineers, business managers, and specialists.
Business
Business managers are generalists with primary focus on on-boarding brands. They are responsible for the integration of inventory and content on Fynd's platform. They interact with all the stakeholders, internal as well as external. They
understand the domain, the end-to-end product activation pipeline, and play a pivotal role in ensuring all the stakeholders are aligned.
Specialists
Contrary to the business role, this pool of individuals come with a core expertise and are divided into the following three categories.
They are our content experts with thorough understanding of the domain, and as such are responsible for defining the Size Guides, and product meta attributes; a majority of this is in the process of being solved by ML models, and while this
is a work in progress, we rely on the meta team to define the problems to be picked by the ML engineers and play a key role in verifying the ML predictions. This is an iterative process and as such the team plays a key role in building
a prediction model with the highest accuracy achievable.
Our image experts are responsible for ensuring that the images and banners being displayed on Fynd adhere to a uniform guideline and add to the aesthetics. This process is tedious and time consuming, and as such the in-house tools such as
picsor; responsible for image validation and upload, have helped us achieve the lowest turn-around-time in processing the images.
Our data experts are one-stop-shop for all the queries related to inventory-content. With a robust knowledge of a variety of databases & visualization tools and products, both open-source & developed in-house, data specialists provided
invaluable analysis, critical to both business and engineering, and in turn helps us in making correct decisions & identify the product-process gaps.
Comprises of individuals with expertise on large scale data curation, machine learning and expertise in programming. Responsible for building the ML workflow, where in the core purpose is automation of product attributes generation, by leveraging
the machine learning models and building a framework to seamlessly train, predict, verify the product attributes.
Responsible for building data pipelines for product masters and near-real-time inventory integration for 100s of brands, and marketplaces. This is our most complex piece of software, is battle tested, has been in production for a couple of
years now. Integrating a brands inventory and content is a matter of few clicks with this system in place.
Responsible for solving business problems by creating products which can be leveraged across teams and domains. Key product focus is on ease of data discovery, exploration, wrangling & sharing. Currently focusing on building a data flow
framework that allows creating data pipelines in a scalable fashion and drag-and-drop UI approach.
- User Experience/Interface:
Responsible for solving business problems by creating products which can be leveraged across teams and domains. Key product focus is on ease of data discovery, exploration, wrangling & sharing. Currently focusing on building a data flow
framework that allows creating data pipelines in a scalable fashion and drag-and-drop UI approach.
