Senior Data Scientist

About the role:

The Senior Data Scientist will bring rigor to strategic initiatives across the Support Organization. As a Senior Data Scientist, you will be a core technical contributor to our Data Science and Analytics team with deep expertise in driving data-driven decision-making, data querying/munging, data visualization, and predictive analytics. You will work closely with Support, Product, and technical teams to translate business questions into quantitative analysis and deliver data-driven strategies.

This role is open to candidates in 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.

• Translate data into strategic insights via memos, presentations, dashboards, etc. to support decision-making for operational and leadership teams 
• Building analytical models to identify patterns, anomalies, and root causes (e.g., analyzing ticket data to proactively identify common customer issues)
• Design and run A/B and other experiments and tests to evaluate AI solutions  
• Build relationships with technical and non-technical stakeholders to understand data structures and business priorities
• Leverage SQL, Python/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:

• Advance degree in Statistics or other quantitative field (e.g., Applied Math, Engineering, Computer Science, Physics, etc.)
• 8+ 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 including Tableau
• 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
• 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 scale models into automated pipelines
• 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)