Middle / Middle+ / Senior Data Scientist

Position: Middle / Middle+ / Senior Data Scientist To: Alfa-Bank, Model Development Department, Retail Business Work format: hybrid — Moscow, Technopark metro station + remote Gross salary range: 200,000 – 400,000 ₽/month

What needs to be done? • Participation in the smart pricing of banking products project as a model developer; • Full cycle of model development: data collection, design and implementation of various model architectures, training, validation, and deployment to production; • Development of models for estimating treatment effects, mainly uplift models; • Analysis of A/B tests and assessment of model impact on business metrics; • Working with large volumes of banking data, creating new features and applying them in models; • Generation and testing of hypotheses, improving model quality, and finding new approaches to solving business problems.

Requirements: • Middle / Middle+ / Senior DS with full-cycle model development experience; • Experience with uplift models will be an advantage; • Deep knowledge of mathematics, probability theory, and mathematical statistics; • Good knowledge of machine learning methods; • Ability to work with data: analysis, cleaning, preparation, selection, and feature creation; • Confident knowledge of Python and libraries for data analysis and machine learning: pandas, scikit-learn, scipy, xgboost, lightgbm, etc.; • Understanding of A/B testing and effect estimation methods; • Ability to connect technical solutions with business tasks and consider the specifics of the domain; • Developed logical thinking; • Hackathon participation experience will be a plus.

What we offer: • Interesting tasks and a friendly team; • Feature Store and AutoML — out-of-the-box baseline solutions; • Automated services for deploying models to production; • Maximum research and minimum bureaucracy and routine; • Opportunity to influence decisions in Alfa-Bank's retail business.

Answers to 10 important questions:

1. Data: usually Hadoop — all Alfa-Bank data + external sources via API. Some data may be in Oracle.
2. Hardware: kuber up to 64 cores + 512 GB RAM. Hadoop — 6TB, 1000+ cores. Production: model execution system + MLOps team. For work: laptop + remote workstation.
3. Scale of influence on core business: models influence key banking processes and product decisions in retail business, including smart pricing of banking products.
4. Level of Data Science development in the company: all business lines are covered by ML models, where necessary — DL is successfully implemented.
5. Role of a data scientist: DS participate in task definition, generate development ideas together with the development team. DS prepare code for deployment to production, and perform service support for users.
6. Background of your manager: Linkedin
7. How often will you be interrupted from working: internal calls with the team and clients, the main focus is on model development, research, and implementation.
8. Career growth: formalized competence matrix. Quarterly "round tables" for review and defense.
9. Prod / Research: Prod 80%.
10. Service or leader function: service/leader — 70%/30%. 📧 Send CV: recruiter contact