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About the position
Watershed is seeking data analysts to transform raw business activity data into final carbon numbers and ensure customers understand how they were calculated. The successful candidate will partner with Customer Success Managers to define data needs, ingest and transform unstructured data sets, use internal tooling to calculate and publish carbon footprint assessments, work with customers to validate uploaded data, and build and augment internal tools and methodologies. The ideal candidate has 2+ years of experience in an analytical and/or customer-facing role, experience writing SQL queries or a quantitative background, is meticulous and detail-obsessed, and is passionate about solving climate change. Watershed is committed to growing a long-term distributed team and has offices in San Francisco, New York, and London.
- Partner with Customer Success Managers to define data needs for each measurement
- Ingest and transform unstructured data sets for processing in automated carbon data pipelines
- Use internal tooling to calculate, test, and publish finalized carbon footprint assessments
- Work with customers to help them upload correct raw data and validate it
- Build and augment internal tools and methodologies to improve analysis, understanding, and validation of user carbon footprints
- Have 2+ years experience in an analytical and/or customer-facing role.
- Have experience writing SQL queries, or have a quantitative background and desire to learn!
- Are meticulous and detail-obsessed. You won't rest until you get the numbers right.
- Are organized, systematic, and efficient. You thrive in a high-volume environment.
- Are willing to roll up your sleeves to work with unstructured and inconsistent data. You have good intuition for how numbers in a table map to the real world.
- Are an excellent verbal and written communicator, and are excited to dig in with our customers as we collect data to measure their footprint.
- Are passionate about solving climate change and excited to contribute to doing so at a fast paced startup.