Are you interested in building and driving the technical vision, strategy, and implementation for Kuiper’s LEO Capacity Management Services? Kuiper is hiring a Principal Data Scientist to help lead the analysis, definition and implementation of our global, highly reliable, predictive data driven services that manage the end-to-end resources of Kuiper’s Internet Service for ground and constellation networks.
A day in the life
You will partner with Product Management, customers, RF, Networking and Beam Planning engineers to understand all capabilities and designs of the Kuiper ISP. You will drive the data driven models of bandwidth, latency and customer segment consumption to create highly reliable, time sensitive, predictive capacity management systems that drive overall monetization and customer experience.
An ideal candidate will have analytical, data science, and system engineering skills to model the interdependent business and technical processes needed to operate and expand a world-wide fleet of space communication and ground assets. The candidate will use these models to enhance customer delight by meeting performance agreements, faster decisions, reduced costs, and simplified interactions.
About the hiring group
The Team is responsible for Architecture, design and delivering and end to end Networking systems for both constellation and ground, as well as the services that utilize the network to delivery last mile and and back-haul internet services. This includes extreme scale of global Software Defined Network and Capacity Management
We are looking for a Principal Data Scientist on this team. You will be responsible for identifying, scoping, and delivering capacity planning solutions with a focus on Europe; based on a deep understand of your customers' needs, you will work closely with senior leaders, scientists, engineers, and business teams worldwide to develop and implement advanced mathematical and economic models and algorithms. You will identify data and science-related bottlenecks, anticipate and make trade-offs, balance business needs versus scientific and technical complexity and constraints, and guide and manage escalations, collaborating closely with multiple teams to ensure the relevance and impact of your work to business stakeholders.
You will need an ability to take large, scientifically complex projects and break them down into manageable hypotheses, design meaningful research questions and analyze the resulting data to inform functional specifications, and then deliver features in a successful and timely manner. You excel at being a thought leader as we chart new courses with our capacity planning technologies, and at defining a vision for products in early stages. Maturity, high judgment, negotiation skills, and the ability to influence and earn the trust of senior leaders are essential to success in this role.
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A Bachelor or Masters Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent experience
10+ years of industry experience in predictive modeling, science and analysis
Previous experience in a ML or scientist role and a track record of building ML or DL models
Export Control Requirement:
Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
PhD in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.)
12+ years of industry experience in predictive modeling and analysis
Good skills with programming languages, such as or C/C++
Ability to experimental and analytic plans for modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
Publications or presentation in recognized Machine Learning, Deep Learning and Mining journals/conferences
Experience with AWS technologies like Redshift, S3, EC2, Pipeline, & EMR
Experience using and/or R
Knowledge of SparkML
Combination of deep technical skills and business savvy enough to interface with all levels and disciplines within our organization
Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment