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Senior Associate Data Scientist - Rev Ops

SAS Institute Inc. - London, UNAVAILABLE, UK

Posted Jun 10, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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Market context

U.S. role benchmark (BLS OEWS)
$111,944 U.S. median for this role
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work
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Application

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Assessment
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Deadline
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Where they hire

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About this role

Senior Associate Data Scientist - Rev Ops London, UNAVAILABLE, UK Senior Associate Data Scientist Remote/ Hybrid- London We're a leader in data and AI. Through our software and services, we inspire customers around the world to transform data into intelligence - and questions into answers. If you're looking for a dynamic, fulfilling career with flexibility and a world-class employee experience, you'll find it here. We're recognized around the world for our inclusive, meaningful culture and innovative technologies by organizations like Fast Company, Forbes, Newsweek and more. About the job T he Revenue Operations Team is looking to hire a Senior Associate Data Scientist to design and deliver analytical solutions for strategic use across the business. This role puts you at the center of revenue‑critical decisions, partnering with Sales and Customer Success to turn data into real business impact. You'll help scale our analytics capabilities while growing your skills in a team that values curiosity, ownership, and authentic collaboration. As a Senior Associate Data Scientist, you will: Lead meetings with division management and our internal customers in other divisions to define the business needs and analytical solutions to drive the business forward. Build data assets. In order to do this you will understand much of SAS's data as it pertains to the analytical requirements of the business. Data assets include 'feature engineering' in order to improve analysis, which can in turn enhance the feature store of revenue operations. Conduct analysis

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