Data Science Manager, Talent Acquisition

Leading the future in luxury electric and mobility At Lucid, we set out to introduce the most captivating, luxury electric vehicles that elevate the human experience and transcend the perceived limitations of space, performance, and intelligence. Vehicles that are intuitive, liberating, and designed for the future of mobility.   We plan to lead in this new era of luxury electric by returning to the fundamentals of great design – where every decision we make is in service of the individual and environment. Because when you are no longer bound by convention, you are free to define your own experience.   Come work alongside some of the most accomplished minds in the industry. Beyond providing competitive salaries, we’re providing a community for innovators who want to make an immediate and significant impact. If you are driven to create a better, more sustainable future, then this is the right place for you.

Lucid is seeking a data-driven Data Science Manager, Talent Acquisition to lead a team of Data Analysts, driving innovation and efficiency across our growing global TA Analytics and Data Insights function. You will build and manage the end-to-end recruiting analytics process, ensuring data integrity, optimizing operational efficiencies, and delivering strategic insights to inform recruiting and broader business decisions.  This role requires strong data science expertise, knowledge of TA or People functions and processes, as well as the ability to lead teams and align work with business strategy. This is an excellent opportunity for an experienced Data Science Lead or Manager with experience in People Analytics or Recruiting Operations.   

This is a hybrid role based out of our Headquarters in Newark, CA.  

You Will: 

• Build and own the end-to-end analytics strategy for global TA, aligning data initiatives with business priorities and workforce planning needs. 

• Lead, grow, and develop the team of Data Analysts driving innovation and measurable impact across the Talent Acquisition lifecycle. 

• Design and operationalize advanced analytics solutions, including predictive models, funnel diagnostics, and automation tools that improve sourcing, selection, and hiring outcomes. 

• Define and evolve TA KPIs, metrics, and success frameworks, ensuring they support business goals, DEI commitments, and operational excellence. 

• Oversee the development and automation of scalable reporting infrastructure using Tableau and other BI tools, enabling real-time insights and self-service analytics for global recruiting teams. 

• Provide executive-level insights and storytelling that influence strategic decisions on headcount planning, talent marketing, and recruiter performance. 

• Ensure end-to-end data integrity across systems by partnering with business owners, IT teams, and external vendors to resolve inconsistencies and drive data governance. 

• Lead cross-functional initiatives with People Analytics, HR Tech, and Talent Operations to scale data-informed recruiting practices and improve stakeholder experience. 

• Establish rigorous QA and data audit processes, proactively surfacing risks, data gaps, and training needs to TA leadership. 

• Champion ethical and responsible use of data, particularly in areas like candidate experience, fairness in AI, and DEI hiring analytics. 

• Research, evaluate and innovate where AI can be utilized to progress TA analytics at Lucid long term 

You Bring: 

• 8+ years of relevant data science experience in People Analytics, Talent Acquisition Analytics, Business Intelligence, or Recruiting Operations.  

• Proven experience leading data science or analytics teams, ideally within Talent Acquisition, HR, or People. Ideally designing a Talent Analytics ecosystem from the ground up. 

• Deep expertise in statistical analysis, predictive modeling, and machine learning, with a strong ability to translate findings into business impact. 

• Advanced proficiency in Python, SQL, and data visualization tools (e.g., Tableau, Power BI); familiarity with data pipeline tools and cloud platforms (e.g., Airflow, Snowflake,