We are looking for a Data Scientist to join our Community Data Team. In this role, you will build applied machine learning models and statistical analyses that help us understand how users discover, evaluate, and interact with deals across Atolls' community platforms.
You will work with rich behavioral data to solve real product and community challenges, from predicting churn to identifying what makes a deal resonate, helping us build smarter products and more useful shopping experiences.
At Atolls, we believe in nurturing both your professional and personal growth. Here's what you can expect:
- A culture that values personal and professional development, with internal mobility opportunities.
- A supportive and open-minded team that embraces diverse perspectives and innovative ideas.
- 32 days of paid vacation plus your birthday off, giving you the time you need to recharge.
- A flexible hybrid working scheme to balance work and life.
- Access to a learning budget and internal training to help you grow in your role.
- Mental health coaching to support your well-being.
- Regular global and local get-togethers to celebrate successes and build connections.
- The possibility of taking a sabbatical after three years with the company.
- A cloud-based company setup, providing flexibility and collaboration opportunities no matter where you are.
- These are global benefits that apply to all employees, with additional local perks based on your location.
In this role, you will:
- Data Science & Modeling: Build and iterate ML models - Churn Prediction, Sentiment Analysis, Member Segmentation, and more — using Python (Pandas, NumPy, Scikit-learn, XGBoost). You will learn and grow through collaboration and code reviews, with the goal of taking independent ownership of models over time.
- Deep-Dive Community Analytics: Analyze complex member behaviors - retention cohorts, engagement velocity, and viral loops — to uncover insights that drive community growth.
- Problem Translation: Take fuzzy, real-world business questions - like "what makes a deal good?" - engage with domain experts, and turn them into something measurable and actionable.
- High-Performance SQL: Master our ClickHouse environment, writing optimized queries that leverage columnar storage to process billions of rows of interaction data.
We're looking for someone with experience in writing complex SQL, investigating web/app event data, and building predictive models in Python, who is dedicated to creating exceptional user experiences and driving innovation.
We hire for aptitude and drive above depth of experience. If you have the right foundation and the right mindset, we want to hear from you.
What we care about most:
- Problem translation: You can take something vague like "what makes a deal good?", talk to the right people, and figure out what to actually measure. For us, this matters most.
- Intellectual honesty: You don't trust your own results just because they look good. You check anyway. This is something we won't compromise on.
- Drive and curiosity: You want to get it right. You dig in, try things, and hold yourself to a high standard, not because someone asks you to, but because that's just how you work.
What you need to bring:
- Solid Python skills and familiarity with core data science libraries (Pandas, NumPy, Scikit-learn) — you can actually build, not just describe
- Sound understanding of ML and statistics fundamentals — core models, train/validation/test splits, overfitting — enough to learn fast under guidance
- Solid SQL skills — comfortable with CTEs, window functions, and writing efficient queries
- At least one self-built, end-to-end project on a messy or open-ended problem — where you had to figure out what "good" meant yourself, not follow a tutorial.
Also valued:
- Signals of applied curiosity — Kaggle, open-source contributions, personal projects or research in recommendation systems or LLMs
- Community Domain Knowledge: Experience analyzing developer communities, forums, or social platforms
- TA Call: Meet one of our Talent Experts and get to know Atolls better.
- Technical Round: Focus on the technical aspects of the role (Through a Live Case), and meet your potential manager.
- Final Round: Meet other Atollians ️
It varies from 1 to 3 interviews
- Some processes might slightly change according to needs
Be part of a destination where your work helps millions of people make better decisions every day.
One focused application is all we need. If you truly fit more than one role, you're welcome to apply to
up to three. This helps us match you with the right opportunity faster.
We review every application with equal care and will reach out if your profile aligns. Apply now with your CV in English.
- Portfolios, writing samples, or certifications may be requested based on the role.
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