Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.
As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.
You are passionate about data and using it to help Rivian on our mission to change mobility. You will take responsibility for populating Rivian’s growing ESS cloud with extremely valuable data we are collecting from our vehicles and other test assets. You will be a primary interface for “Extract-Transform-Load” activities for Rivian ESS’s Data Science team, which is a vital activity in transitioning raw data to usable data in our cloud. You are meticulous and detail-oriented, but you can also operate on challenging timelines. You know how to manage priorities, even when you are told everything is needed “now”. You can also operate well under pressure, for those few cases where something really is needed “now”. You have experience with data at large scales, and you know how to process the data to make it usable and quickly retrievable.
- Create fleet-level monitoring ETL jobs
- Develop Energy Storage Metrics – Collaborate with stakeholders (including ESS Data Science, other ESS teams, and other stakeholders outside ESS) to define useful metrics of battery operation. Some may be obvious, while others arise from collaboration.
- Implement ETL for Energy Storage – Develop data storage approaches for ETL that blend search response time criteria with fidelity requirements of the search. The balance of speed vs time will depend heavily on the needs of the analysis, response time, as well as the physics of the data
- Deploy ETL Tasks – Collaborate with stakeholders to deploy critical jobs, including those that will be safety-related. Ensure that capabilities or jobs are vetted and tested before deploying
- Support Critical Issue Resolution for High-Profile Assets
- Root Cause Analysis – Support Engineering team in root cause analysis by providing data support to help identify potential similar issues or causes for issues in data.
- Fleet Analysis – Work with multiple stakeholders, as needed, to pull vehicle data from multiple vehicles for fleet-level analysis. Goal is to either learn about, or protect, Rivian’s prototype vehicles by standing up new capabilities for ETL based on data, in many cases on new signals recently added by BMS.
- Create streaming jobs for real-time, ESS-related fleet metrics
- Develop Metrics – Collaborate with vehicle-facing stakeholders in ESS and other organizations to develop metrics for real-time vehicle monitoring. Balance data processing time/resources, fidelity, and other criteria to optimize
- Implement and Deploy – Implement real-time streaming jobs based on stakeholder needs. Test and verify capability are ready, including reporting or display method. Deploy to vehicle in collaboration with stakeholders.
- 3+ years’ work experience in data science performing ETL and data analysis on large datasets (terabyte to petabyte scale)
- Strong Python coding skills, with experience with quantitative libraries (specifically including Pandas) required
- Experience with databases such as SQL and NoSQL required
- Strong cloud experience, preferably AWS, required
- Degree in Computer Science, Electrical Engineering, Mathematics, Chemistry, or Chemical Engineering preferred
- Strong quantitative skills required
- Strong communication skills required
- Strong experience or degree in a physical science preferred
- REST API experience preferred
- Experience with Kubernetes, EMR, or cluster computing/management is preferred
Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law.
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