Kepler is a radical innovation lab working in the world of investment management. We build and invest in radical innovations with the potential to disrupt institutional asset management. As an autonomous division of GIC, one of the world’s largest sovereign wealth funds, our group is nimble, and innovative in spirit, but with the backing to tackle monumental projects and have enormous impact.
We are looking for a Backend Engineer to help build innovative Machine Learning products for large-scale institutional investing.
You've got an interest in machine learning and the ability to build impactful solutions at a massive scale. Always willing to roll up your sleeves in order to find results, you thrive in a collaborative environment where you’re always being challenged to find solutions to unique problems.
Job description/Role Responsibility:
- Own and drive requirements throughout the software development lifecycle for large components of a machine learning based investing product, including architecture/design, implementation, testing, and launch
- Lead design discussions on data models, architectural framework, and business logic
- Lead backend strategy for data flows as well as model and backtesting modules
- Work with your teammates in an unstructured environment to solve diverse technical challenges
- Partner with various teams to leverage existing and new technologies, integrating them to create a seamless experience for our users
- Help build and shape our engineering culture
- 4-6 years of experience as a backend engineer
- Good interpersonal, oral and written communication and collaboration skills
- Expert knowledge of Python
- Ability to write reusable code using best practices (unit tests, commentary etc) independently
- Ability to work closely with our client's internal teams.
- Eagerness to tackle big problems that have unknown solutions at the outset
- Passionate about solving challenging problems and iterating quickly
- B.S., M.S., or Ph.D. in Computer Science or related field
- Strong track record of academic or professional achievement
Nice to Have’s
- Backend experience in a high growth fintech environment
- Machine Learning product development experience
- Experience working with Spark/Hadoop databases and SQL (basic to intermediate knowledge)
- Strong familiarity with large-scale data requirements