5 year of experience with Python 3
5 year of experience in Scientific Python stack like Numpy, SciPy, Pandas is a must
Strong understanding of calculation complexit, numerical stability of simple (linear) algorithm
Ability to detect/reduce errors and/or complexity of the simple algorithm
Strong knowledge of model evaluation and benchmarking techniques and corresponding standard
Strong knowledge of statistical forecasting models, ML algorithms, features generation and validation
At least Upper Intermediate English Level is a must
Good business communication skills
Knowledge of the following: Matlab/Octave, R is a plus
Knowledge of Economic Simulations and Actuarial Calculations is a plus
Understanding theoretical concepts of statistics/probability is a must
Understanding theoretical concepts of data mining, machine learning is a must
Ability to work independently with limited supervision
Ability to handle multi-tasking activities
Ability to learn quickly
Master degree in Mathematics, Physics, Computer Science or similar
Above average compensation and competitive Social package
Close cooperation with a customer
Business trips
Challenging tasks
Competence development
Team of professionals
Dynamic environment with low level of bureaucracy
Getting insight into business problem, understanding the opportunity and value of analytical models for the customer
Collecting, transforming and preprocessing raw data to prepare it for analysis
Deriving descriptive statistics out of the preprocessed data
Building statistical and probabilistic models
Designing, developing, training and testing data mining, machine learning and artificial intelligence models and algorithms
Providing comparative research on different algorithms and models
Implementing the model in a form that can be easily used by engineers, documenting its interfaces
Delivering the model in a form that can be easily deployable and maintained
Our project is a cloud-enabled, scalable, and award-winning High Performance Computing enterprise risk management solution that allows (re)insurers and pension funds to access next generation technology to rapidly solve today’s key insurance challenges such as hedge strategy testing, regulatory and economic forecasting.