We’re looking for an experienced CRM System Administrator to manage, customize, and optimize our CRM platform in line with business goals. The ideal candidate will collaborate with cross-functional teams to improve system performance, enhance user experience, and deliver valuable insights that support Customer Support operations and business decision-making.

Responsibilities:

• Understand Customer Support operations, challenges, and goals, improving processes through CRM administration and consultation. 
• Manage and optimize CRM settings, including user permissions, workflows, custom objects, reports, dashboards, and approval processes. 
• Administer virtual phone systems, AI solutions, integrations, APIs, and third-party tools to ensure smooth cross-functional operations. 
• Analyze system and team performance data to provide operational insights and improve productivity. 
• Collaborate with teams to gather business requirements, implement solutions, and support troubleshooting, training, documentation, and data integrity.

Requirements:

• Strong experience in CRM administration, including permissions, workflows, custom architecture, and system optimization. 
• Knowledge of virtual phone systems, AI tools, APIs, integrations, and third-party platforms. 
• Advanced skills in formulas, data validation, reporting, dashboards, and data integrity management. 
• Ability to analyze business needs, improve operational workflows, and implement cross-functional solutions. 
• Experience in troubleshooting, user support, training, and documentation. 
• English level: B2+ (Upper-Intermediate/Advanced).

Key skills:

• Comfortable working in a fast-paced, changing environment with a focus on continuous process improvement. 
• Strong analytical, problem-solving, communication, and organizational skills with the ability to work independently and cross-functionally. 
• Detail-oriented and highly organized. 
• Experience configuring CRM platforms such as Salesforce, Intercom, Freshdesk, or similar; experience with self-hosted CRM systems is a plus. 
• Previous experience with CRM systems in the trading or iGaming industry is preferred. 

Benefits:

• Quarterly bonuses based on Company performance
• 24 working days of annual leave 
• Corporate events and team building activities
• Udemy Business unlimited membership & language training courses 
• Professional and personal development opportunities in a fast-growing environment

We are looking for a Data Science specialist with experience in banking projects to build risk models (scoring for lending).

Key Areas of Responsibility

Risk Modeling Department:

- Full-cycle development of ensemble models, including data preparation and preprocessing, labeling, and splitting into training and testing datasets.  

- Selection and tuning of base models with an emphasis on diversity to improve prediction quality.  

- Development of machine learning models to forecast daily balances on corporate client accounts, incorporating time series analysis (weekly, monthly, quarterly) and additional factors (weekdays, holidays, tax periods, business cycles).  

- Training personalized models.  

- Application of model aggregation techniques (bagging, boosting, stacking) with optimized ensemble weighting.  

- Performance evaluation using accuracy, recall, and F1-score metrics to enhance prediction quality.  

- Deployment of models into production environments, ongoing monitoring, and regular parameter optimization.

Computer Vision Projects:

- Development and implementation of a biometric identity verification system, including document recognition and photo comparison modules.  

- Requirements analysis and system architecture design with a focus on high security and recognition accuracy standards.  

- Implementation of image processing algorithms to extract data from passports and compare with client selfie photos.

Acquisition Analytics:

- Comprehensive analysis of acquiring and cash management portfolio data, including collection and preprocessing of historical client behavior data.  

- Feature engineering reflecting transactional activity, financial indicators, and service usage patterns to identify key churn factors.  

- Building and training an ensemble prediction model optimized for the specifics of both products.  

- Implementation of client scoring system based on churn probability considering financial behavior and length of partnership.

Technologies and Tools: Python, SQL, Scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow/Keras, PyTorch, Random Forest, Gradient Boosting, Stacking, Pandas, NumPy, Matplotlib, Seaborn.