TBC Bank Group PLC established Space International with the strategic aim of facilitating the group's global expansion efforts. In 2018, the team successfully introduced the pioneering neobank, Space, in Georgia. Building upon this success, subsequent efforts were directed towards the creation and launch of the fully digital bank in Uzbekistan, TBC UZ, in 2020. In a significant move towards enhancing its foothold in the Uzbek market, the group acquired Payme, a prominent local payments provider and esteemed brand among the Uzbek populace, in 2023.
Presently, a dedicated team of 3,000 professionals representing 17 nationalities collaborates to advance TBC's international presence. Space International spearheads the provision of cutting-edge technologies and top-tier professional services, while the local teams at Payme and TBC Uzbekistan drive sustained growth and operational excellence.
We are looking for talented individuals with Machine Learning Engineer experience to join our team.
Primary Focus:
- Model Deployment and Integration: Familiarity with deploying machine learning models in a production environment and integrating them into existing banking systems.
- Cross-Functional Collaboration: Work closely with engineering, data science, DataOps and product teams to ensure seamless integration of machine learning models into operational workflows and business processes.
- Implement data pipelines for preprocessing, feature engineering, and model evaluation.
- Monitor and optimize model performance in production, ensuring scalability and robustness.
Qualifications:
- Proven Experience in ML Model Development: Hands-on experience with developing machine learning models in production for large-scale data environments in the banking sector (e.g., credit scoring, fraud detection).
- Supervised Learning: Deep understanding of models like logistic regression, decision trees, random forests and gradient boosting machines (GBM) for predictive tasks such as credit risk assessment and loan default prediction. Expertise in classification techniques like SVM, k-NN, and Naive Bayes for tasks like customer segmentation and risk categorization.
- Knowledge of SQL and experience with data warehousing solutions.
- Data Wrangling and Feature Engineering: Expertise in transforming raw data into usable formats and crafting features suitable for machine learning models.
- Familiarity with MLOps tools (e.g., MLflow, Kubeflow).
- Solid grasp of version control tools (e.g., Git) and CI/CD practices.
- Experience with containerization tools (Docker).
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.
- Big Data Technologies: Proficiency in working with Apache Spark, Hadoop, or other distributed computing frameworks to process large datasets efficiently.
- Real-time Model Training: Familiarity with real-time model training techniques, including online learning and incremental learning, to update models continuously as new data becomes available, ensuring up-to-date predictions for dynamic banking environments.
- Languages: English - B2; Russian - A2 (Will be a plus)
Nice-to-Have:
- Real-time Model Monitoring: Experience in monitoring performance of deployed models using technologies such as the ELK Stack, Prometheus, Grafana, and ClearML.
- Experience working in Banking industry
- Experience with NLP, computer vision, or deep learning techniques.
What We Offer:
- Full support and career-development resources to maximize your potential along our career journey
- Market competitive total compensation package
- 100% company-paid for every employee’s medical insurance
- Benefits and incentives to stay healthy and fit
- English language classes
- Possibility to be involved in an international project
- Junk Fridays, fruit days, terrace BBQs, and many more
Thank you for your interest in opportunities at JSC 'Space International.' Your privacy is a priority. We process data in compliance with the Law of Georgia 'On Personal Data Protection.' Your information is confidential and used solely for assessing suitability, with a maximum 2-year retention period. We securely store your data using BreezyHR (Canada). You are authorized to request data deletion or modification, or provision of information regarding data processing. If you have any such requests or have any questions regarding data processing, please feel free to contact us ProfileModificationRequests@ space.ge. Our commitment extends to equal treatment, ensuring a fair and unbiased selection process. Thank you for considering opportunities with us.