Мы команда NIX: нам уже 25 лет, однако этот солидный возраст совсем не повлиял на наше умение весело работать и дружно отдыхать . NIX — это 2000 девелоперов и тестировщиков, дизайнеров, аналитиков требований, Sales и Project менеджеров, и многих, многих других классных IT-специалистов из Харькова.
8 апреля 2021

Strong middle Python Developer ‒ Data Engineer (PySpark) (вакансия неактивна)


Необходимые навыки

• Strong programming skills in Python;
• Experience with Spark/PySpark;
• Familiar with Agile software development practices;
• English level—Intermediate.

Будет плюсом

• Experience with AI/ML;
• Excellence in technical communication with peers and non-technical people alike;
• Experience in test-driven development practices;
• Development for Kubernetes;
• Experience with AWS or any other cloud provider.


• Challenging projects from worldwide leaders in different business domains;
• Skilled management and mature processes;
• Competitive compensation and extra bonuses for excellent results;
• A friendly team and legendary corporate parties;
• Comfortable workspace in the city center;
• Medical, sports and accounting support programs.


• Rewriting legacy algorithms using Spark to process big data in a timely fashion;
• Building infrastructure to train models and keep them up-to-date, ensuring quality monitoring and re-training with newer historical data;
• Building reusable components for the ETL;
• Optimizing the quality and performance of the new ML models and algorithms based on prototype and closely working with a subject matter expert (SME) from the customer side.

О проекте

The customer provides multiple software solutions for the healthcare industry. Innovative solutions are powered by advanced technology and help optimize costs, reduce risk, support compliance processes, enhance customer engagement, and create additional revenue streams.

The customer already owns a platform that can run various predictive models based on historical data. The platform need to extend the offering with new analytics tools that will help hospitals and insurance companies analyze and predict the probability of the following actions:
• Cost-efficiency of treatments in comparison with others in the industry
• Risk of mortality based on the patient’s condition, diagnosis, and treatment path
• Discovering typical patterns per distinct groups of patients
• Identifying extra costs spent on services or additional penalties when there was no procedure
• Predicting complications based on patient condition and similar historical data of other patients
• Considering all the risks determine if a patient requires hospitalization or outpatient treatment can be successful
• Prediction of how long the specific patients will stay at the hospital to forecast hospital costs