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Data Scientist, Recruiting Operations
Company | Tesla |
Address | , Palo Alto, Ca |
Employment type | FULL_TIME |
Salary | |
Expires | 2023-07-23 |
Posted at | 11 months ago |
What to Expect
What To Expect
What You’ll DoWhat You’ll Bring
Overview
We are seeking a highly skilled individual to lead our Recruiting organization's data strategy and lay the groundwork for data storage and access. This role involves collaborating with a diverse range of stakeholders, including recruiters, hiring managers, developers, and analysts. The ideal candidate will possess a deep understanding of the entire Recruiting and HR data landscape and have the ability to contextualize data in meaningful ways. As a key member of our team, this person will enjoy a high degree of autonomy to drive the successful implementation of our data storage and distribution strategy from the ground up.
What To Expect
Tesla's Recruiting Systems + Analytics Team is seeking a versatile candidate to work collaboratively with recruiters, developers, and hiring teams. As a foundational member of the team, the ideal candidate will support full-stack data engineering and analytics throughout the Recruiting organization. The team is also responsible for liaising with stakeholders and maintaining the company's recently launched, fully- integrated, customizable applicant tracking system.
The successful candidate will play a critical role in ensuring that data is at the center of every decision made within the Recruiting organization. The job involves building data pipelines and creating infrastructure to collect and organize data. This data is used to derive insights about the recruiting process and drive the evolution of Tesla's in-house systems. The role requires a generalist who can work across the entire data engineering and analytics stack, with a focus on supporting the Recruiting organization's objectives
- Ensure data quality and automate identification of quality issues
- Process raw, structured, semi-structured, and unstructured data using batch and real-time frameworks
- Document process and approach for continuous improvement
- Suggest and implement infrastructure improvements
- Build new data pipelines to support reporting infrastructure
- Collaborate with development teams and analysts to identify and solve issues
- Audit and refine existing pipelines for accuracy
- Refine data collection, storage, consumption, and documentation methods
- Plan data security, sharing, and publishing within the organization
- Knowledge of DevOps and a bias for automation
- Strong written and verbal communication skills
- Experience building Python-based ETLs
- Ability to work independently in unstructured environments
- Strong background in data modeling, access, and storage
- Knowledge of Recruiting or People data is a plus
- Experience with data visualization tools such as Tableau or Apache Superset
- Strong problem-framing, problem-solving and project management skills
- Understanding of SQL + NoSQL database systems
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