Data Scientist
You’ll join an environment where growth, learning, and creativity are encouraged. Flexible schedules, trust-based workflows, and a supportive team give you everything you need to focus on your best work.
🇺🇦 Proudly Ukrainian, Skylum stands with Ukraine through action, regularly supporting organizations that help accelerate our victory.
We’re looking for a Data Scientist to understand user behavior and develop machine learning models that improve user experience, product adoption, retention, and purchasing conversion.
You will join our Core Analytics team and collaborate with Data Engineers, Analytics Engineers, and Product and Marketing analysts. You will identify meaningful behavioral patterns, turn them into predictive features, and train models that support personalization and better product decisions.
Our data environment:
Python, SQL, Apache Airflow, MySQL, ClickHouse, Parquet, AWS, and Tableau.
Why join us:
You will help shape applied data science within Core Analytics and influence how our products respond to user needs. Your work will turn behavioral data into models and experiences that help users discover value, adopt relevant features, and make repeat purchases.
Experience delivering data science or machine learning solutions with measurable product or business outcomes.
Strong Python skills for data preparation, feature engineering, model training, and evaluation using pandas, NumPy, scikit-learn, and related libraries.
Strong SQL skills for analyzing event-level data and building reliable modeling datasets.
Practical experience with classification, regression, clustering, and gradient boosting methods such as XGBoost, LightGBM, or CatBoost.
Experience identifying behavioral patterns and creating predictive features from user activity, event sequences, purchase history, and lifecycle data.
Knowledge of the full model lifecycle: target definition, dataset preparation, hyperparameter tuning, validation, deployment, monitoring, and retraining.
Strong understanding of statistics and experimentation, including data leakage, class imbalance, selection bias, temporal validation, and prediction calibration.
Familiarity with deep learning concepts and a clear understanding of when neural networks offer value over simpler approaches.
Experience with Git, reproducible workflows, and collaboration with engineers to productionize models.
Ability to translate business goals into modeling problems and explain findings, limitations, and recommendations clearly.
Explore user journeys, habits, and behavioral patterns to identify signals associated with adoption, engagement, upgrades, repeat purchases, and churn.
Define prediction targets and develop features, labels, and training datasets from product events, transactions, and customer data.
Train, tune, and evaluate machine learning models for purchase propensity, customer lifetime value, churn risk, and next-best actions.
Develop segmentation, recommendations, and personalization models; apply deep learning where the problem and available data justify it.
Partner with engineers to deploy models and integrate predictions into product experiences and business workflows, including monitoring and retraining.
Validate business impact through experiments, distinguishing predictive relationships from causal effects and balancing conversion with user satisfaction and long-term retention.
Hands-on experience with PyTorch or TensorFlow.
Experience with recommendation systems, ranking, embeddings, or sequential models for user behavior.
Knowledge of uplift modeling and causal inference to identify which interventions improve outcomes for different users.
Experience with subscription, mobile, or marketplace products, including upgrade propensity and repeat-purchase prediction.
Familiarity with Airflow, ClickHouse, AWS, experiment tracking, feature stores, and model monitoring.
For personal growth:
- A chance to work with a strong team and a unique opportunity to make substantial contributions to our award-winning photo editing tools;
- An educational allowance to ensure that your skills stay sharp;
- English, German and Polish classes to strengthen your capabilities and widen your knowledge.
- A great environment where you’ll work with true professionals and amazing colleagues whom you’ll call friends quickly;
- The choice of working remotely or in our office space located on Podil, equipped with everything you might need for productive and comfortable work.
- Medical insurance;
- Twenty-one days of paid sick leave per year;
- Twenty-one days of paid vacation per year;
- Fun times at our frequent team-building activities.
What to expect when you apply
- An interview with our Talent Acquisition Manager
- Professional interview
- Technical interview
- Interview with CEO
- And finally, your job offer!