Explorium is a cutting-edge data science company that has recently closed a Series B round bringing their total funding to $50 million.
Explorium offers a first of its kind data science platform powered by augmented data discovery and feature engineering. By automatically connecting to thousands of external data sources and leveraging machine learning to distill the most impactful signals, the Explorium platform empowers data scientists and business leaders to drive decision-making by eliminating the barrier to acquire the right data and enabling superior predictive power.
We are looking for a delivery-oriented, experienced software engineer to join our core backend team and develop our AI based data science platform. Our offering spans from a SaaS application to an on-premise deployment on high-profile enterprises.
As part of the team, you will extend our ability to onboard enterprise customers, to match the challenges they are facing, and ensure proper engagement and adoption of our platform.
In this role you will use cutting-edge technologies to develop scalable services that form the backbone of Explorium’s platform.
- Developing new features and backend infrastructure enhancements on Explorium’s data science platform.
- Engaging in problem analysis and collaborating with product and development teams to create feature plans that outline implementation details.
- Understanding business priorities, participate in feature design and incremental delivery of a SaaS application.
- Working in an Agile environment, at a sustainable pace, in two-week sprints.
- Have 3+ years experience in backend or infrastructure development of enterprise-grade web applications.
- Have backend development experience working on a SaaS web application, preferably in Python.
- Believe testing and code quality are important, and promote an effective code review.
- Like to move quickly and iteratively, and believe that shipping early is best.
- Are proactive and enjoy working on cross-functional delivery teams.
- Like to start new things, see them through to production, and learn from your mistakes.
- Have experience in an on-prem deployments.
- Have worked with Kubernetes or other container-based operational environments.