Data Science Engineer

About Quvia:
Quvia is building the digital fabric between edge and cloud. Our platform uses AI and machine learning to orchestrate connectivity across satellite, terrestrial, and hybrid networks so customers can move and manage data in the world's most network constrained environments.
We partner with global leaders in aviation, maritime, energy and other industries where connectivity is variable and complex, and digital services depend on reliable data movement. As companies deploy AI, automation and data-driven systems at the edge, Quvia provides the platform needed to unlock the full potential of their data and build value above the network.
Quvia is a fast growing, Series A company backed by Colombia Capital ($5B+ in fund commitments. It is headquartered in the greater Miami area with offices in the UK and India.
Learn more at www.quvia.ai
and www.linkedin.com/company/quvia.
Why Quvia?
Founded in 2019, we are a fast-growing, Series A tech startup passionate about making connectivity experiences better for everyone.
Our industry-first solutions are already addressing major challenges for companies in the travel and transportation industries–and we’re just getting started.
As an early-stage company’s new hires will have the opportunity to make a significant impact on our growth trajectory.
We are headquartered in the greater Miami region, with remote teams spanning the U.S., Europe and India.
Quvia is backed by Columbia Capital, a respected venture capital firm founded in 1989 that has raised over $5 Bn of fund commitments.
About the Role
We're looking for a Data Science Engineer to work on the NextGen connectivity platform across platforms. This is an outstanding opportunity to help build an ambitious future for our flagship product.
We’re seeking curious thinkers looking to co-author the next chapters of our story. Joining now means helping shape our vision, structures, and systems; playing a key-role as we launch into our ambitious future.
What You'll Do:
Lead Data Science Initiatives: Guide a high-performing data science team in
creating scalable and impactful data solutions for product development. Drive the
design and implementation of analytics frameworks that include predictive and
prescriptive modelling, with an emphasis on data quality and security.
Data Strategy & Integration: Identify high-impact datasets and embed insights,
such as anomaly detection and knowledge graphs, directly into products.
Collaborate with engineering to integrate these insights seamlessly, enhancing
product functionality and responsiveness.
Advanced Modelling to Build Products: Develop models that address complex
product requirements, including forecasting, classification, and prescriptive
modelling. Use machine learning, optimisation, and neural networks to create
products that proactively adapt to changing needs and deliver robust user
experiences.
Model Deployment & Adaptability: Ensure models are production-ready, scalable,
and adaptable to real-world product demands. Partner with engineering to deploy
and continuously refine these models, keeping them aligned with evolving
requirements.
Quality Assurance & Data Governance: Implement rigorous validation and data
quality standards to ensure consistency and reliability across products. Maintain
data governance practices that support secure, compliant usage.
Documentation & Knowledge Transfer: Develop and maintain comprehensive
documentation of data workflows, model design, and deployment processes.
Facilitate knowledge sharing to support both technical and non-technical teams.
Mentorship & Team Development: Mentor junior data science team members in
advanced analytics and modelling techniques, fostering best practices and
collaborative problem-solving.
What You'll Need:

Employment type
Full Time

Work arrangement
No