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.

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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:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Operations
  Research, or a related field.
• Minimum of 5 years of experience in data science, focusing on product-driven
  solutions, including forecasting, classification, and optimization.
• Proficiency in machine learning and optimization modeling, with a strong
  understanding of analytics tools (Python, SQL) and experience with neural networks, transformers, and knowledge graphs.
• Experience in generative AI using LLMs, with a proven ability to integrate these
  technologies into data-driven products.
• Strong analytical and problem-solving skills, with the ability to structure
  data-driven solutions to complex product challenges.
• Excellent communication skills, adept at simplifying technical concepts for diverse
  stakeholders and fostering cross-functional collaboration.
• Proven leadership skills with the ability to mentor and guide junior team members.
• Commitment to continuous learning, staying current with advances in data science
  and machine learning.
• Collaborative mindset, contributing positively to cross-functional efforts.

What We’ll Offer

● Collaborative and innovative work environment

● Aviation, Maritime domain exposure, and business knowledge

● Connectivity and content engineering and business knowledge

● Opportunity to work in cross-functional teams.

● Competitive health benefits that start on day one

● Generous paid time off policy

● Enterprise Product end-to-end experience with direct customer feedback

● Performance-based bonus

● Opportunity to work across teams and organizations.

Quvia is an Equal Opportunity Employer. Employment opportunities at Quvia are based upon one's qualifications and capabilities to perform the essential functions of a particular job. All employment opportunities are provided without regard to race, religion, sex (including sexual orientation and transgender status), pregnancy, childbirth or related medical conditions, national origin, age, veteran status, disability, genetic information, or any other characteristic protected by law.

Quvia will never ask to interview job applicants via text message or ask for personal banking information as part of the interview process.

Quvia will never ask job applicants or new hires to send money or deposit checks for the company.