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ML Engineer
Senior
All, Armenia, Cyprus, Kazakhstan, Poland
TATECH-17779
- Master's or Ph.D. in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field;
- 5+ years of experience in applied machine learning and data science;
- Deep understanding of classical machine learning algorithms, statistical modeling, and data analysis techniques;
- Expertise in time series analysis, tabular data modeling, uplift modeling, and user segmentation;
- Strong proficiency in Python for data science and ML implementation;
- Solid grasp of data structures, algorithms, and software engineering principles;
- Experience with AWS and its data science and ML services;
- Knowledge of big data technologies (e.g., Spark) for large-scale data processing;
- Familiarity with MLOps principles and tools for model deployment and monitoring;
- Excellent analytical and problem-solving skills.
- Experience applying ML/data science in gambling or gaming industries;
- Familiarity with causal inference, Bayesian methods, and probabilistic graphical models;
- Knowledge of ethical AI and fairness in machine learning;
- Experience with A/B testing and experimental design;
- Proficiency in MATLAB or R for additional statistical computing and analysis;
- Understanding of deep learning techniques and their applications to tabular data.
- Strong analytical and critical thinking skills;
- Ability to convey complex technical concepts to both technical and non-technical audiences;
- Data-driven decision-making approach;
- Collaborative mindset for cross-functional projects;
- Self-motivated with the ability to work independently on long-term projects;
- Adaptability to evolving business needs and data science landscape;
- Attention to detail and commitment to producing high-quality, reproducible analyses.
- Design and implement machine learning models for time series forecasting, churn prediction, and customer lifetime value estimation;
- Develop and apply uplift modeling techniques to optimize marketing campaigns and personalization strategies;
- Conduct user segmentation analysis to inform product development and marketing strategies;
- Create and maintain data pipelines for feature engineering and model training;
- Collaborate with data engineers to ensure efficient data processing and storage;
- Develop and implement A/B testing frameworks to evaluate the impact of ML models and features;
- Optimize existing ML models to improve performance and scalability;
- Stay current with the latest developments in data science and assess their applicability to our business needs;
- Work closely with product and business teams to understand challenges that could benefit from data science solutions;
- Ensure all models and analyses adhere to ethical AI principles and gambling regulations;
- Contribute to the company's data science knowledge base and foster a culture of data-driven decision making;
- Mentor junior data scientists and share best practices within the team.
- Programming Languages: Python (required), R (preferred);
- ML Libraries: Scikit-learn, XGBoost, LightGBM, Prophet, statsmodels;
- Data Processing: Pandas, NumPy, Spark;
- Visualization: Matplotlib, Seaborn, Plotly;
- Cloud Platform: AWS (primary);
- AWS Services: SageMaker, Athena, Redshift, EMR;
- Version Control: Git;
- MLOps Tools: MLflow, Airflow;
- Experimentation Platforms: Optimizely, AWS A/B Testing;
- Big Data: Familiarity with Hadoop ecosystem.
- 🍀An exciting and challenging job in a fast-growing product ecosystem, the opportunity to be part of a multicultural team of top professionals in Development, Engineering and Architecture, Management, Operations, Marketing, etc;
- 🤝Great working atmosphere with passionate IT experts and leaders, sharing a friendly culture and a success-driven mindset is guaranteed;
- 📍Beautiful offices in Kyiv, Warsaw, Limassol, Almaty, Yerevan – work with comfort and enjoy the opportunity to build a network of connections with IT professionals day by day;
- 🧑💻Laptop & all necessary equipment for work according to the ecosystem standards;
- 🏖Paid vacations, personal events days, days off;
- 🫖Paid sick leave;
- 👨⚕Medical insurance;
- 💵Referral program — enjoy cooperation with your colleagues and get the bonus;
- 📚Educational support by our L&D team: internal and external trainings and conferences, courses on Udemy;
- 🗣Free internal English courses;
- 🤸♀Sport benefit;
- 🦄Multiple internal activities: online platform with newsletters, quests, gamification and presents for collecting bonuses, PIN-UP talks club for movie and books lovers, board games cozy evenings, special office days dedicated to holidays, etc;
- 🎳Company events, team buildings.
— Do you want to fulfill your dream? Take your career to the next level with PIN-UP — create trends, don’t follow them.
Oksana Izmailova
CHRD PIN-UP GLOBAL