Senior Data Science Engineer (offline)

Job Description
3+ years of experience analyzing large volumes of data
Knowledge of R and Python and key data science libraries
Experienced in model fitting and forecasting
Excellent analytical skills and strong statistical knowledge, as well as interest in applying them to complex problems
Extensive experience solving analytical problems using quantitative approaches
A passion for empirical research and for answering hard questions with data
A flexible analytic approach that allows for results at varying levels of precision
Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
Upper-intermediate English
Exploratory data analysis, hypothesis testing, data preparation, and product prototyping based on modern statistical and ML/AI methods
Use systems and internal processes efficiently and integrate these in daily work
Clear communication of insights and findings to stakeholders
Job Responsibilities
The candidate will work on one of the Data products helping to develop data processing components for the currently built data pipeline. Work with London (PO, Data Scientists) and Ukraine teams
The candidate will work in 2 teams, Data and Dev team. The Dev is dedicated to helping with software engineering aspects for the pipeline. Data has 6 people with one data scientist and two data analysts involved in the project. The Dev team has 3 software engineers with one 100% involved in the project. Data processing components will be written in Python mainly using Pandas (potentially ML tools) and integrated with a developed kubeflow based data pipeline. Data will be stored in GCP and use mainly csv, spss and excel files and possibly expand integration with a database.
The candidate will help with building in Python elements of the pipeline. Datasets will have in total a few GB of data per quarter. There are multiple components of the pipeline at various stages of development, such as QA checks, reporting, dashboard data preparation, adding additional aggregated variables, data ascription. The candidate will communicate delivery requirements with the Data team and engineering details with the Dev team.
It is expected that the candidate would have strong pandas and python data wrangling skills and an understanding well general software engineering practices including coding, documentation, and software versioning.