Data Scientist

O projekcie: We offer: - Stable employment. On the market since 2008, 1500+ talents currently on board in 7 global sites. - Workation. Enjoy working from inspiring locations in line with our workation policy.  - Great Place to Work® certified employer. - Flexibility regarding working hours and your preferred form of contract.   - Comprehensive online onboarding program with a “Buddy” from day 1.    - Cooperation with top-tier engineers and experts.   - Unlimited access to the Udemy learning platform from day 1. - Certificate training programs. Lingarians earn 500+ technology certificates yearly.  - Upskilling support. Capability development programs, Competency Centers, knowledge sharing sessions, community webinars, 110+ training opportunities yearly. - Grow as we grow as a company. 76% of our managers are internal promotions.   - A diverse, inclusive, and values-driven community.    - Autonomy to choose the way you work. We trust your ideas.   - Create our community together. Refer your friends to receive bonuses.   - Activities to support your well-being and health. - Plenty of opportunities to donate to charities and support the environment.   - Modern office equipment. Purchased for you or available to borrow, depending on your location. Wymagania: - commercial experience with various classical data science and Machine Learning (ML) models (e.g. decision trees, ensemble-based tree models, linear regression etc.) - knowledge of customer analytics concepts or advanced forecasting - model hyperparameter tuning - in an analytical role supporting business will be a plus - fluency in Python, basic working knowledge of SQL - knowledge of specific DS/ML libraries - solid experience in one of the cloud computing platforms (Databricks or GCP or Azure) Nice-to-have: - understanding of Causal machine learning - experience in working with big data and distributed environments would be a plus - commercial experience proven by multiple successful projects in the areas of forecasting would be a big plus - Experience with OOP in Python - Experience with MLOps - familiarity with other languages R, Scala would be a plus General: - basic computer programming skills and familiarity with programming concepts - strong business acumen - experience with deep learning, reinforcement learning or other advanced modeling concepts in classical Data Science problems Codzienne zadania: - Work on end-to-end classification and forecasting use cases: problem framing, data preparation, model development, evaluation and basic deployment support (e.g. demand forecasting, churn prediction) - Explore and clean data; perform EDA to understand data and flag data quality issues. - Engineer features for tabular and timeseries data. - Train, validate, and tune standard ML models (e.g. logistic regression, treebased models, gradient boosting, simple neural nets, classical timeseries models). - Evaluate models with appropriate metrics that have impact on business KPIs. - Build clear visualizations and concise reports to present model results and insights to business stakeholders. - Collaborate with data engineers and AI engineers to bring models into production (batch scoring, APIs, models monitoring, dashboards). - Document data sources, modeling assumptions, and experiment results in a reproducible way (notebooks, reports, wikis).