Mar 27, 2023
As the center of the Business Data Science division, our team will include you. Working together with commercial data science researchers, your aim will be to put their concepts into practice. The research team will provide the model prototype to you, and it is your responsibility to turn it into an accurate model. The whole life cycle of a machine learning project falls within the purview of the machine learning team. When a model is produced, its life officially begins. Not only will you be in charge of the model's deployment, but also of its serving, upkeep, and supervision. We offer migration support, and legal help for you and your family (if relocating)
Review and understand the data, including checking logic and cleaning outliers as needed.
Carry out feature engineering, using different techniques of feature preparation, transformation, normalization, or generation.
Conduct model training and evaluation, developing Kubeflow pipelines for model training and experimenting.
Carry out model deployment, create Argo workflow pipelines to run models in production.
Be responsible for model monitoring and maintenance—after the model is ready, our goal is to monitor its metrics to understand when we should interfere and update the model.
MS degree in computer science or a similar field or demonstrable working experience in software engineering
3 or more years of industry experience in software engineering in Python
Ability to build applications and familiarity with best practices such as CI/CD, testing, and coding standards
3 or more years in the machine learning experience
Deep understanding of classic models like linear regression, logistic regression, or gradient boosting decision trees
Good understanding of mathematical statistics and probability theory
Strong knowledge of SQL, including complex queries and analytic functions
Experience with cloud platforms such as AWS and Google Cloud
At least an upper-intermediate level of English
Nice to have:
Experience with Argo and Kubeflow
Competitive and attractive compensation
Extensive learning opportunities, such as professional training and certifications, soft skills development, free English courses, and trading workshops
Flight tickets, hotel or apartment accommodation for your first month, migration support, and legal help for you and your family (if relocating)
Health and life insurance for employees, spouses, and children, including vaccinations, tests, mental health care, and coverage for vision and dental care
Generous time off, including 21 days of annual leave and paid sick leave
Education allowance for your children’s school and kindergarten fees
Access to our very own sports club with dedicated coaches, free Sanctum Club memberships for you and your spouse, corporate SUPs, jet skis, etc
A branded company car (if relocating) with a parking space near the office
Outstanding team-building experiences and Exness community gatherings
First interview (up to 40 minutes)
Capability test (1 hour)
Test task (5 days)
Final interview (1 hour)