Position: Head of Data Scientist Line
Company: UKRSIBBANK
Experience required: 5y
English level: upper

**Key responsibilities:**
1.	Team leadership and management of the two data scientist;
2.	Technical and Scientific referent to diagnose / arbitrate / correct difficult problems and support data scientists;
3.	Participate in the elaboration of advanced analytics use cases / projects:
•	Data requirements, data source identification, gathering, quality control; might be cleaned and governed data source to complex to access data or non present data that would require to design strategy to acquire (open data or web gathering, data acquisition, new product to propose to gather the data); all this under strict respect of compliance and legal framework (with help of data office);
•	Feature engineering in potentially complex configuration (like transforming time series of events into features);
•	Modelisation: find appropriate modelling strategy (algorithm selection, model architecture, model quality check and analysis, verification of results with business (are feature and tests sound from a business perspective); include temporal stability analysis in some cases; include more or less detailed documentation of the model(s);
•	Prototype: organize live tests (A/B testing, light implementation approach), analyze results and confirm economic or business interest of the use case;
•	Implementation support for IT / business.
4.	Innovate and share
•	Propose new ideas to improve existing use cases or create new one;
•	Run R&D project to explore new ideas or technologies;
•	Follow up trends: academic research in some specific domain useful for the bank;
•	Attend BNP group analytics community event and propose content.

**We offer:**
•	Interesting job in a friendly team;
•	Competitive salary;
•	Health insurance;
•	Professional and career development;
•	Benefit from being part on international community.

**Requirements:**
•	Higher education
•	Strong theoretical knowledge on machine learning algorithm (logistic regression, tree based models, ensemble models, boosting techniques, GAM and GLM) and neural network techniques (deep learning with CNN or NLP); candidate should be able to choose appropriate models based on constraints (transparency & explanability, model implementation and available IT environment, available data) and not only on pure performance metrics, and to explain choice and results; people with only experience with auto-ML tools excluded de facto;
•	First significant practical usage of these skills (5 years of experience in these skills);
•	Capacity to communicate in English / Ukrainian oral and written at good level;
•	Capacity to quickly understand new business fields and interact with business representatives;
•	Good programming experience in python (scikit, capacity to produce industrial code and not only notebooks), development in agile mode with devops, unit testing tools;
•	Business and social orientation: proud of having a financial gain for the company and/or positive impact on society;
•	Specialization on one field of application (NLP, voice, credit scoring, marketing models, fraud, etc.);
•	Experience in financial services;
•	Curious and passionate for data, mathematics and business;
•	Basic knowledge of regulatory requirement around data, or ability to quickly ramp up on it;
•	More languages: French, Polish, Russian, German, Turkish.