SoftConstruct conducts basic and applied research in four key areas: data science, computer vision, big data, real-time processing. Our experience is extremely wide: from working with complex computer and engineering systems, programming for data science — to developing and putting into practice innovative solutions in the field of sports, eSports, and security.
Project: Data Platform.
Data warehouse that delivers the performance, simplicity, concurrency, and affordability for data collecting, rapid analytics, and extracting data-driven insights for business users.
Lambda architecture, designed to handle massive quantities of data by taking advantage of both batch and stream-processing methods. This approach to architecture attempts to balance latency, throughput, and fault-tolerance by using batch processing to provide comprehensive and accurate views of batch data, while simultaneously using real-time stream processing to provide views of online data.
In many organizations, data consumption processes for timely reporting or crucial analytical requirements are hindered by both delays in query execution and information presentation. The main challenge is to minimize decision delay with help of flexible solutions with open and simplified architecture and high performance based on future-oriented technologies using AI models and forecasting analytics.
Up to 1 PB of data from 500+ partners in long-term storage
30+ M new records daily
Latency for insight based on data delivery time <5 sec
Technologies: SQL, Google BigQuery, Google Colab, Metabase.
— 1+ years of experience as BI/Data Analyst;
— Hands-on experience with data visualization tools;
— Solid data visualization principles understanding;
— Business analysis: Marketing, Operations, Finance areas
— Data analysis: SQL, basic statistics, EDA, anomaly detection, clustering problems etc.
— VCS: git, Bitbucket;
— OS: Linux.
Nice to have:
— Domain in Gambling area (SportsBook or casino);
— R or Python;
— Familiarity with data storage and ETL pipelines;
— Hands-on experience with Google Cloud Platform: Cloud Storage, BigQuery etc.
— Data collection and preparation;
— Building analytic dashboards (mostly using Metabase, Grafana, Kibana);
— Collaboration with the team Backend, Data Engineers, FrontEnd, Data Science, Design;
— Creation and support of project documentation;
— Corporate DWH and data science workbench integration.
— Interesting and challenging work in a product and data-driven company;
— Plenty of opportunities to learn, grow and progress in your career;
— We keep work-life balance;
— Health insurance;
— Free English classes;
— Paid vacation 24 days and paid sick leave;
— Silent office near Lukyanivska metro station;
— Participate in R&D projects.