Knowledge of time series analysis, probability theory and statistics, factor analysis, and optimization.
Basic knowledge of actuarial calculation and InsurTech terms understanding (underwriting, claims, premiums).
Previous experience with economic/finance data search, analysis, and model building, knowledge of ML algorithms, and data analysis approaches.
Understanding how these theoretical concepts could be applied to real-world problems
Ability to understand the nature of business problems and see the place of analytical models in the solution
Strong English verbal and written communication skills
Great analytical skills
Ability to work independently with limited supervision
Ability to handle multi-tasking activities
Ability to learn quickly
Initiative and pro-active skills, and flexibility
Above average compensation and competitive Social package
Close cooperation with a customer
Ability to influence project technologies
Projects from scratch
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
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 customer is one of the biggest insurance companies in the USA. In cooperation with the developing team, we will be working on the pipeline of POCs with the visual and data/modeling part. POCs are aimed at validating future products and services of the company.