THE PURPOSE:

The Data Scientist / Analyst will be part of the Machine Intelligence and Analytics team. This team sits within our Systems Development organization and will be responsible for establishing and maintaining the architecture and analytics to ensure data is usable in a real-time manner between the pod, tube, track, etc.

THE ROLE:

• Perform extract, transform, and load operations on large datasets from many complex, heterogeneous data sources
• Explore, interpret, and analyze datasets for patterns of interest and opportunities for incorporating data driven machine intelligence to vehicle, transportation, and logistics software systems
• Research, evaluate, and determine the best fit of analytical tools and techniques
• Develop or modify existing machine learning tools and libraries as needed
• Develop visualizations of key parameters and relationships to provide insight into data and underlying system.
• Develop, evaluate and adapt advanced machine learning algorithms to transportation and logistics problem domain
• Design and create data mining architectures/models/protocols, statistical reporting, and data analysis methodologies
• Enhance, scale, and deploy real-time analytics capabilities, models, and visualizations within production environment on production compute architecture
• Develop metrics and evaluation criteria to characterize and quantify system performance and benefits of machine intelligence
• Develop, update, and maintain design specification and end user documentation
• Collaborate in a fast-changing environment and to communicate clearly and effectively with colleagues who range from data scientists, developers, dev ops, hardware engineers, and product managers.

CANDIDATE PROFILE:

• Strong written and oral communication skills.
• Strong interpersonal skills.
• Ability to conduct research into issues and products as required.
• Ability to present ideas in user-friendly language and visuals.
• Highly self-motivated and directed.
• Keen attention to detail.
• Proven analytical and problem-solving abilities.
• Ability to effectively prioritize and execute tasks in a high-pressure environment.

MINIMUM REQUIRED EXPERIENCE:

• Bachelor’s degree in Computer Science or a highly quantitative discipline.
• Strong programming ability with Java, Python, and web based technologies
• Strong knowledge in software engineering principles
• Fast prototyping skills, including comprehensive feature integration during all cycles of development
• Hands on experience and expertise with cloud computing services (AWS, Azure, etc.)
• Working knowledge in manipulating large datasets and performing data analytics with machine learning tools.

PREFERRED EXPERIENCE:

• Master’s degree or PhD in Computer Science or a highly quantitative discipline.
• Strong mathematical foundation in statistics and linear algebra
• Strong programming ability with C, C++
• Experience with relevant open source, commercial, and scientific software packages
• Working knowledge of Computer Vision, Artificial Neural Networks, Bayesian Networks, Markov Decision Processes, Support Vector Machines, and other cutting-edge machine learning methodologies.
• Experience with the following software packages: CUDA, Tableau, OpenCV, ROS, TensorFlow, Café, Alchemy, SAS, Genie, Deep Dive, PostgreSQL, NoSQL, Apache products (Spark, Hadoop, Hive, etc.)
• Ability to provide solutions to a variety of technical problems of increasing scope and complexity
• Domain expertise and knowledge of transportation, logistics, and autonomous systems

Hyperloop One is an Equal Employment Employer; employment is governed on the basis of merit, competence and qualifications and will not be influenced in any manner by race, color, religion, gender (including pregnancy, childbirth, or related medical conditions), national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability or any other protected status. Hyperloop One will consider qualified applicants with criminal histories consistent with the “Ban the Box” legislation.