Intersog® is a Chicago-based provider of ROI-driven custom web and mobile development specializing in delivery of full-service, end-to-end solutions and project resources to Fortune 500 companies, SMEs and startups. We help our clients attack their ambitious business goals, solve skills shortage issues and become innovative by building Dedicated Software Development Teams in Ukraine and/or providing on-demand IT project resources to complete required skills on their in-house teams.
Our primary goal in partnering with our clients is to exceed their expectations and foster an ongoing relationship that envelopes innovation, industry leadership and business strategy while delivering products that bring exceptional user experience, brand elevation and market dominance.
- 2+ years of professional experience working as a Big Data Engineer;
- 3+ years programming on Java, Scala or Python;
- 2+ years of professional experience with AWS Big Data Technologies like Redshift, DynamoDB, S3, Athena, Kinesis, Lambda;
- 2+ years of experience in Spark;
- High SQL level;
- Advanced level of English.
Bonus if you have:
- Working experience with graph databases (Neo4j).
- Opportunity to work on challenging and exciting international projects;
- Competitive salary based on your skills, experience, and customer satisfaction;
- Casual, positive and open work environment;
- Opportunity to advance career and grow as a professional;
- Long-term employment with 24-28 paid calendar vacation days;
- Paid personal or sick leave day’s scheme;
- Friendly team and flat organizational structure;
- Regular knowledge sharing meet-ups and events;
- English lessons with a native speaker.
We use state of the art machine learning and mathematical modeling to create credit risk models for clients in emerging markets, based on data extracted from a client's smartphone. We work in a Kaggle like environment, where any improvement to our model directly translates to revenues. We are also recognized as positively influencing our target markets, by giving credit to an otherwise unbanked population.