Staff Data Scientist, Connectivity Data and Insights

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

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.

The Connectivity team is seeking a Staff Data Scientist who can work on cross-functional team and lead the effort of building data insight generation services from ground up. As a Staff Data Scientist, you will partner closely with product managers, engineers, and other scientists to research, deep dive, experiment, and build data science solutions in the Connectivity domain. You will explore the data and zoom out to think holistically. You will be responsible for providing insights to the business teams and fostering a data-driven decision-making culture to establish the data science foundations in the organization.

This is what you’ll do:

• As a Connectivity Data Scientist, you will partner closely with Product and Software development team to understand and solve critical business questions and develop the data architecture and methodologies needed to execute quantitative assessments needed on connectivity. 
• Design, implement and analyze experiments to improve the performance of the systems. 
• Deliver end-to-end data science solutions including understanding the business need, exploring data, building & validating machine learning models, deploying the completed models to Production, and measure success. 
• Handle all steps in the model development lifecycle – Data exploration, analysis, data wrangling, model development, training, experiment, and iterations. 
• Create accurate and statistically sound summary metrics to evaluate Connectivity health and derive insights. 
• Design and develop secure, scalable, high-performance, and reliable data platform for vehicle connectivity health. 

This is what you’ll need:

• Advanced degree in engineering, mathematics, computer science, or related discipline preferred with 6+ years of relevant industry experience. 
• Experience with statistical data analysis and machine learning such as linear models, time-series forecasting, or neural networks. 
• Proficient in Python, SQL, Scala, or similar programming languages for data exploration. 
• Proficient working with large volume of both structured and unstructured data.
• Proven track record of solving business challenges by providing insights through the lens of data science. 
• Deep knowledge of AWS technologies on big data.
• Comprehensive knowledge of modern data science and product analytics tools and techniques such as Python, Machine Learning, advanced statistics, and data mining techniques. 
• Ability to work in a fast-paced environment and work both independently and collaboratively with other data engineers. Ability to thrive in ambiguity.