Compensation Overview

About the role:

This Senior Data Scientist will measure, evaluate, and conduct measurements on our AI/ML systems. As a Senior Data Scientist, you will partner with ML scientists and engineers to develop methodologies to measure and evaluate our production models, conduct experiments to understand how new models compare to old ones and contribute to data-driven product development. You will work with other data-minded individuals to bring cutting-edge AI to our customers.

This role can be fully remote in US or Canada.

You should apply if:

• You want to impact the industries that run our world: The software, firmware, and hardware you build will result in real-world impact—helping to keep the lights on, get food into grocery stores, and most importantly, ensure workers return home safely.
• You want to build for scale: With over 2.3 million IoT devices deployed to our global customers, you will work on a range of new and mature technologies driving scalable innovation for customers across industries driving the world’s physical operations.
• You are a life-long learner: We have ambitious goals. Every Samsarian has a growth mindset as we work with a wide range of technologies, challenges, and customers that push us to learn on the go.
• You believe customers are more than a number: Samsara engineers enjoy a rare closeness to the end user and you will have the opportunity to participate in customer interviews, collaborate with customer success and product managers, and use metrics to ensure our work is translating into better customer outcomes.
• You are a team player: Working on our Samsara Engineering teams requires a mix of independent effort and collaboration. Motivated by our mission, we’re all racing toward our connected operations vision, and we intend to win—together.

Click here to learn about what we value at Samsara. 

In this role you will:

• Develop metrics and methods to understand and develop our AI/ML systems.
• Run experiments and causal analyses to evaluate and launch new AI/ML features.
• Build relationships with technical and non-technical stakeholders to understand data structures and business priorities.
• Leverage technologies like SQL, Python, and/or R to shape and analyze data.
• Build a strong sense of product and data acumen (e.g. customer experience, data logging).
• Stay connected to industry and academic research and adopt novel technology that suits Samsara’s needs.
• Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices.

Minimum requirements for the role:

• PhD in a quantitative field (e.g., Statistics, Applied Math, Engineering, Computer Science, Physics, Biology, Psychology, Political Science, etc.), or Masters with equivalent experience.
• Experience with analyzing AI/ML products and systems. 
• 5+ years experience in a data-related role relevant (data science, data analyst, business analytics, business intelligence).
• Proficiency in data manipulation and processing in SQL, Python, and/or R.
• Experience building statistical and other analytical models, preferably in Python or R. 
• Ability to communicate trends and learnings via data visualizations.
• Ability to effectively share project statuses and take ownership of tasks while handling competing priorities.
• Ability to distill informal or ambiguous customer and business requirements into crisp problem definitions.
• Proven ability to communicate verbally and in writing to technical peers and leadership teams with various levels of technical knowledge.
• Strong communication skills (both verbal and written).
• Curious about our data, our product and excited to have an impact.

An ideal candidate also has:

• PhD in Statistics or other quantitative field.
• Ability to build advanced statistical models for understanding correlation and/or causation.
• A strong track record of cross-functional partnership. 
• Record of successful mentoring and development of team members.
• Experience working with large datasets using distributed computing (e.g., Spark, Hive).