Description
The Sber AI Department for Artificial Intelligence and Machine Learning Development (Sber AI), Directorate for AI Initiatives Implementation and Promotion, is seeking a Data Scientist to implement AI/GenAI projects in the B2G segment. As part of our friendly team, we help the government drive disruption in public administration through the implementation of AI/GenAI and accelerate the national development of AI/GenAI. We organize one of the world's largest specialized events – AI Journey – bringing together business, government, and the international scientific community to ensure the country's GenAI transformation.
Responsibilities
- Development and validation of ML models, creation and implementation of AI/GenAI solutions for B2G
- Designing architecture for AI/GenAI and ML models to address business tasks
- Formalizing business tasks into ML problem statements, selecting quality metrics and success criteria
- Data collection, analysis, and preparation (EDA), feature engineering
- Conducting experiments, comparing approaches, interpreting results, preparing recommendations for the client
- Data analysis, feature engineering, A/B testing
- Participation in deploying models to production: collaborating with engineers, preparing artifacts (specifications, data/service requirements)
- Monitoring model quality after launch, proposing retraining and improvements
- Preparing technical documentation and results presentations
- Interaction with business clients and technical teams
- Mentoring junior specialists (if a team is present)
- Managing individual streams of AI/GenAI projects (within one's area of responsibility)
Requirements
- Ability to solve ad-hoc tasks beyond standard product development approaches
- Higher technical/mathematical/economic education
- Work experience as a Data Scientist / ML Engineer / Applied Researcher from 2 years
- Proficient in Python and SQL; experience with leading LLMs and ML libraries
- Understanding of the full lifecycle of an ML model
- Knowledge of main approaches to model quality assessment, handling class imbalance, overfitting, interpretability
- Experience deploying ML models to production (Docker, FastAPI, MLflow, Airflow/Prefect, CI/CD) and working with real-world data (quality, missing values, anomalies), ability to document the pipeline
- Communication skills: ability to explain technical solutions to business stakeholders, experience in cross-functional collaboration (analysts/development/architecture/security)
- English proficiency at Upper Intermediate level or higher
Will be a plus:
- Public cases/portfolio (GitHub, Kaggle, articles/presentations)
- Technical/mathematical higher education from MIPT or HSE
Conditions
- Top-tier, world-class research tasks
- Comfortable, modern office near Kutuzovskaya metro station
- Hybrid work format
- Annual salary review. Annual bonus
- Corporate gym and relaxation areas
- Over 400 educational programs from SberUniversity for professional and career development
- Adaptation program and manager support at the start
- Extended voluntary health insurance, preferential family insurance, and corporate pension program
- Flexible mortgage discount equal to 1/3 of the Central Bank's key rate
- Free SberPrime+ subscription, discounts on partner companies' products
- Referral bonus for recommending friends to join the Sber team.
