Remote | Data Scientist - Monetization team

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

The Data Science for Monetization team at OLX Group is responsible for unlocking hidden value using data and artificial intelligence. We analyse the status quo, improve buyer & seller interactions, optimize the user experience and monetize on the delivered customer value. For us revenue growth is the good fruit of our work and not the goal itself.

We invite you to join a team which works with OLX, Automotive platforms (Otomoto, Standvirtual) and Real Estate platforms (Otodom, Storia) across the entire EU region. A team that breaks through walls and builds cross-functional connections with everyone around. A team where a common mission and goals matter more than reporting lines. We build on each other, asking for help and support when needed, and we proactively support others.

In your day to day routine you will have the opportunity to develop supervised models for behavioral classification, deep learning models for image classification, regression models for value estimation as well as NLP models for object and actor entity recognition. All in Python and the AWS cloud. You will be exposed to key stakeholders, having direct contact with internal customers. You will have the carte-blanche to experiment and test things. And most importantly, you will also witness how your work impacts the day to day business of OLX Group customer units.

What you will be doing:

• Your primary role will be to increase business value by finding opportunities where data science and machine learning can make an impact.
• You will maintain strong relationships with stakeholders. This means asking a lot of questions to business people, 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.
• You will build models, tinker around them to make them work, test them and eventually deploy to production. You will see your stuff in action and you will be able to measure the true impact of your models.
• 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 are we looking for:

• Analytics and Modeling:
• Very strong analytical skills. Like really strong! So strong that truth and light are your two middle names.
• Solid background in statistics and modeling.
• Good knowledge of Python, which means having experience with at least one of the following: Scikit-Learn, TensorFlow, PyTorch, Pandas.

Machine Learning Engineering:

• Good understanding of engineering best practices, that is: testing, CI/CD, monitoring, alerting, containers.
• Hands-on experience with SQL.
• Ability to work with big data at scale: experience with columnar storage clusters.

Stakeholder Management:

• Proficient in English with excellent written and oral communication skills!
• Strong presentation skills.
• Able to work in multi-functional teams with people from different backgrounds.

Nice to have:

• Deploying models to production and serving models at scale.
• Using AWS for deploying machine learning solutions.
• Building data pipelines using tools like Spark and Airflow.
• A/B testing.

What we offer:

• Permanent contract with 50% KUP.
• Annual bonus of 15% of your base salary.
• Strengths-based personal career development.
• Company mobile phone, MacBook Pro or Windows Dell along necessary accessories to make your work comfortable.
• Competitive compensation and benefits (medical care, sports package and others).
• Training and conference budget.
• The opportunity to learn from each other and become better every day.
• A passionate and diverse team of data scientists spanning across several tech hubs in Europe and around the world.