This job might no longer be available.
Magic Leap is seeking an ambitious, self-directing data scientist leader to join the Core Data team. This role will be responsible for leading our data science and machine learning team and drive the technical and process roadmap for the organization.
Primary Responsibilities:
- Operate with the ability to guide, influence, and inspire innovation & adoption of data science and advanced analytics solutions and insights.
- Serve as primary technical lead in the design and implementation of solutions leveraging machine learning and artificial intelligence.
- Provide unique, independent perspectives to seemingly disparate data with the goal of moving from inquiry to insights.
- Use data-mining tools and techniques to collect, compile, manipulate and transform structured and unstructured data from a wide variety of internal and external data repositories.
- Partner with the business and product teams to identify the most important data-driven questions, define structured use cases, and develop initiatives to provide answers.
- Provide qualitative and quantitative data support to ensure accuracy of characteristics and metrics.
- Logically integrate information from multiple resources and effectively communicates results to department management and business stakeholders.
- Use data visualization tools to develop visuals that can be used to effectively communicate technical findings to a non-technical audience.
- Collaborate within and across teams to improve the ways in which key data streams are captured, managed, and made accessible for analysis.
Preferred Qualifications:
- 15+ years of experience in hands-on experience in predictive modeling and large data analysis.
- 5+ years leading a data science team / organization
- Expert level experience in applying statistical methods and data science techniques to analyze data, build predictive models, glean insights and tell stories with data.
- Expert in machine learning methodologies (i.e. supervised learning, unsupervised learning, reinforcement learning)
- Deep experience in natural language processing (i.e. text translation, sentiment analysis, speech recognition)
- Deep experience with AWS and GCP cloud stacks
- Deep experience with R, Python and SQL.
- Experience with quantitative analysis techniques (e.g., predictive modeling, clustering, classification, regression).
- Experience with visualization tools
- Exceptional data analysis, critical thinking, communication, problem solving and cross-group collaboration skills.
- Record of delivering large analytical solutions with big business impact.
- Ability to address abstract business and engineering problems with extreme precision.
Education:
Bachelor’s degree (Master’s degree preferred) with concentration in a quantitative discipline such as Mathematics, Statistics, Economics, Computer Science or Operations Research preferred.