Natcast (short for The National Center for the Advancement of Semiconductor Technology) is a new, purpose-built, non-profit entity created to operate the National Semiconductor Technology Center (NSTC) consortium, established by the CHIPS Act of the U.S. government.
Working at Natcast represents an opportunity to help extend America's leadership in semiconductor technology, significantly reduce the time and cost of moving from idea to commercialization, and build and sustain a semiconductor workforce development ecosystem.
These efforts to advance semiconductor technology and seed new industries built on the capabilities of a wide range of advanced chips hold the potential to benefit the country and the world for generations to come.
Principal Data Scientist, Workforce Center of ExcellenceIn this pivotal role, you will lead all data science activities for Natcast's and the NSTC's Workforce Development efforts, reporting directly to the Senior Manager of Workforce Insights. As the Principal Data Scientist, you will be instrumental in leveraging advanced analytics to drive evidence-based decision-making and shape the future of the semiconductor workforce in the United States.
Every day, you will collaborate closely with the Workforce Business Systems Analyst to build robust data environments, perform sophisticated data modeling, and extract actionable insights that inform and enhance our workforce development initiatives. Your expertise will be crucial in addressing the critical skills gap in the semiconductor industry and supporting Natcast's mission to advance U.S. leadership in semiconductor design and manufacturing.
To thrive in this role, you must possess exceptional data science skills, a deep understanding of workforce analytics, and the ability to translate complex data into strategic recommendations. Your work will directly impact the development of a skilled semiconductor workforce, contributing to the nation's technological leadership and economic security.
The Workforce Center of Excellence (WCoE) is dedicated to developing and implementing innovative programs to build a skilled semiconductor workforce, collaborating with industry partners, educational institutions, and government agencies.
The Principal Data Scientist plays a crucial role in the WCoE's mission by providing data-driven insights that shape our workforce development strategies and programs, ensuring they effectively address the evolving needs of the semiconductor industry.
Responsibilities:Lead the design and implementation of data science projects focused on workforce development in the semiconductor industry.Develop predictive models to forecast workforce needs, skills gaps, and industry trends.Create and maintain a comprehensive data environment for workforce analytics, ensuring data quality and accessibility.Collaborate with the Workforce Business Systems Analyst to integrate various data sources and build efficient data pipelines.Perform advanced statistical analyses and machine learning techniques to extract meaningful insights from workforce data.Develop data visualization tools and dashboards to communicate complex findings to stakeholders effectively.Work closely with cross-functional teams to translate data insights into actionable workforce development strategies.Provide technical leadership and mentorship to junior data scientists and analysts within the WCoE.Stay abreast of emerging trends in data science and workforce analytics, recommending innovative approaches to enhance our capabilities.Contribute to the development of data governance policies and best practices for the WCoE.Collaborate with industry partners and academic institutions to leverage external data sources and research findings.Present findings and recommendations to senior leadership and external stakeholders.Required Skills and Experience:Ph.D. or Master's degree in Data Science, Statistics, Computer Science, or a related field.7+ years of experience in data science, with a focus on workforce analytics or related fields.Strong proficiency in programming languages such as Python, R, or Julia for data analysis and modeling.Expertise in machine learning techniques, statistical modeling, and predictive analytics.Experience with big data technologies (e.g., Hadoop, Spark) and cloud-based data platforms (e.g., AWS, Azure).Proficiency in data visualization tools (e.g., Tableau, Power BI) and ability to create compelling visual narratives.Strong understanding of data governance, privacy, and security best practices.Excellent communication skills, with the ability to explain complex technical concepts to non-technical audiences.Proven track record of leading data science projects and delivering actionable insights.Preferred Qualifications:Experience in workforce development, labor market analysis, or human capital analytics.Familiarity with the semiconductor industry or other high-tech sectors.Knowledge of educational data analysis and program evaluation methodologies.Experience working with government agencies or in public-private partnerships.Publications or presentations in relevant fields of data science or workforce analytics.If you are a passionate data scientist with a keen interest in workforce development and the semiconductor industry, eager to contribute to a mission of national importance, we encourage you to apply for this position. Join us in our efforts to build a robust and skilled workforce that will drive the future of semiconductor innovation and manufacturing in the United States.
Natcast is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, gender expression, age, national origin, disability, marital status, sexual orientation, military status, or any protected attribute. We encourage qualified candidates from all backgrounds to apply and join us in our mission. If you require accommodation at any stage of the application process due to a disability, please let us know.
We collect and manage personal data in compliance with data privacy regulations and best practices.
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