Data Scientist

NEW YORK
ENGINEERING
FULL-TIME

RYLTI's engineering teams face unique technical challenges of scale and complexity. By enhancing the ability of engineering teams across RYLTI to make data-driven decisions, our team of Data Engineers help define and evolbe RYLTI's core products, cloud platform and tools.

Responsibilities

  • In partnership with product engineering leaders, Data Engineers are responsible for identifying issues with our engineering workflows, iterating on improvements, and measuring their impact across RYLTI — all through analysing and contributing back to RYLTI's internal data platform. Data Engineers are given direct ownership of key areas of focus for RYLTI's business, and delivering meaningful change is their primary measure of success.
  • You will write code to transform noisy real-world data into high-signal models that stand the test of time.
  • You will excavate the hidden insights in RYLTI's internal data that will revolutionise our business strategy. At your fingertips is RYLTI's cutting-edge data management, integration, and analytical platform, eliminating common data management obstacles such as data duplication, questionable data provenance, and fragmented collaboration.

What We Value

  • Intellectual curiosity and creativity.
  • A background in science or engineering, especially in fields such as Mathematics, Physics, Computer Science, or Software Engineering..
  • Excellent communication skills.
  • Previous experience in a role that requires rigorous financial or business analytics.
  • Comfort in a fast-paced environment. Able to consistently revise approach in response to new information.
  • Proficiency with programming languages such as Python, R, Java, or similar languages.

About RYLTI

The RYLTI team is comprised of leaders in the fields of enterprise software, machine learning, data science, mathematics, and music industry applications with a common vision and belief that a massively scaleable application framework combined with the latest advances in machine learning can be applied to quantitatively enable applications that are not possible with current technologies alone. If this type of technology and related projects excite you, we'd love for you to join us.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Benefits