Role overview
*WELCOME TO OLX
At OLX, we work together to build a more sustainable world through trade**.
We make it safe, smart, and convenient to buy and sell cars, find housing, get jobs, buy and sell household goods, and more. Our colleagues around the world help to serve millions of people around the world every month, through its well-loved consumer brands including OLX, Otodom, AutoTrader, Property24.
What you'll work on
- Work in the Data Science team from a platform and marketplace perspective.
- You will build models, tinker around them to make them work, test them, and eventually deploy them to production. You will see your stuff in action, and you will be able to measure the true impact of your models (less expected, yet a requirement)
- You will maintain strong relationships with stakeholders. This means asking a lot of questions to business people and translating their requirements into achievable projects. It also means collaborating with other teams, like infrastructure and data engineering, to get things done in an elegant and timely manner.
- Partner with Engineering and Product to deliver solutions (customer-facing and platforms) to our customers (internal and end customers)
- Work with Product Analytics to track the KPIs of different ML use cases and measure the impact on our customers.
- Partner with the Experimentation team to integrate the KPIs and their proxies into the Experimentation (A/B testing) platform.
- You will work in multi-functional teams, in a diverse, multinational environment, filled with people from Portugal, Bulgaria, Romania, Poland, Ukraine, Kazakhstan, and Uzbekistan.
- Most importantly, you will have fun working with us :)
What we're looking for
- Exposure to other programming languages such as Kotlin, Java, Scala, etc
- Experience bringing models into production and serving models at scale
- Experience using AWS for deploying machine learning solutions
- Experience with building data pipelines using tools like Spark and Airflow
- Understanding of A/B testing and experimentation
- Exposure to MLOps tools
Interview process
- Recruiter Interview
- Hiring Manager Interview
- Technical Interview
- Take-home Exercise
- Panel Interview
Tags & focus areas
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