Job description
StyleNook is a fashion - tech startup that is making fashion wearable and accessible to the urban working woman. StyleNook takes the concept of a personal shopper (someone who knows you really well), makes selections on your behalf, and has you try things on! They combine data science and a human stylist to curate a box of clothes and accessories based on the user’s preferences.
Access the Stylenook LinkedIn page on the following link; https://www.linkedin.com/company/stylenook/
Access the Stylenook official website; https://stylenook.in
Key Responsibilities
- Core Personalisation Algorithms: Working on cold-start recommendations, collaborative filtering models, the incorporation of feedback to enable customer satisfaction, etc.
- Operations Efficiency: Leveraging our data to understand what products to procure, and where to enable or disable deliveries in order to reduce the return rate and improving overall efficiency.
- Inventory Forecasting and Demand Predictions: Leveraging demand patterns, external factors, and user feedback to influence inventory and supply decisions.
Does this Sound Like You?
Must Haves:
- Bachelor's degree in Computer Science, Data Science/Data Analytics, Math/Statistics or any other related discipline.
- High level of proficiency in R, Python, Scala or similar modelling/scripting language.
- One year work experience required in an analytical area.
- Strong hands-on knowledge in statistics, optimisation, predictive modelling and data analysis/trend analysis.
- Comfortable with SQL and no-SQL databases.
- Knowledge of product recommendation algorithms such as collaborative filtering and clustering algorithms.
Preferred:
- Ability to make sense out of a variety of data and its relation/applicability to the business problem or opportunity at hand.
- Ability to both formulate/understand the business problem at hand as well as ability to discuss with non data-science background stakeholders.
- Able to deal with ambiguity and competing objectives.