Head of Risk
Key responsibilities include:
  1. Initiating and developing new approaches for customer analisis
  2. Introducing efficient lending procedures
  3. Coaching managers involved in Lending
  4. Credit portfolio and risk analysis, and recommending corrective actions
  5. Organizational capacity and managerial competence
Main requirements:
  • Knowledge of the methodology for assessing the borrower's risks in online
  • Development of scoring cards for various loan products
  • Development and maintenance of documentation of the process of creating / monitoring the work of the scoring card
  • Knowledge and skills in statistics, mathematical modeling
  • Development of automated reports for quality control of the scoring model
As a plus:
  • Experience with SQL (PostgreSQL)
  • Experience with Python (Pandas, Numpy, Scikit-learn, Scipy, etc)
Data Scientists
Data Scientists work with the risk-management and marketing teams to develop client relationships and deliver data science solutions for effective decisions. You will need to be comfortable leading technical demonstrations of SynergyOne, helping us develop models that add value to our projects, and integrating those models into project’s environments. Ideal candidates enjoy day-to-day data science problem-solving mixed with high levels of customer interaction.
Key responsibilities include:
  1. Build, test and validate predictive models
  2. Deliver high quality code and documentation
  3. Working with a mixed set of technologies and experimenting with new ones
  4. Exploring how state-of-the-art machine learning methods can be applied to our product
Main requirements:
  • Strong skills in exploratory data analysis
  • Experience with SQL (PostgreSQL)
  • Experience with Python (Pandas, Numpy, Scikit-learn, Scipy, etc)
  • Experience with machine learning concepts: regression and classification, clustering, feature engineering\selection, ensembling\stacking etc.
  • Familiarity with statistical concepts
As a plus:
  • Achievements on platforms for data science competitions (Kaggle, DrivenData, etc.)
  • Experience with data visualization tools and packages
  • Experience with version control systems (Git)
  • Experience with R
  • Experience with NoSQL (Redis)
  • Experience in deployment with Docker
  • Familiarity with CRISP-DM
  • Experience in building scoring models
  • Financial or banking background