Remote Data Engineer III

Summary

Join Zuora Platform tech as a core member of the AIMS team (AI, ML and science) to leverage the latest AI technologies to enable total monetization for Zuora. As a data scientist/machine learning engineer, you will identify $ opportunities, build stakeholder relationships, simplify complexity through technical expertise, and take end-to-end ownership to deliver results.

Requirements

• 5+ years of experience in the data science/machine learning domain, preferably with hands-on end-to-end model building experience
• Strong data engineering background, with ETL experience, building and maintaining pipelines, data modeling, data warehousing concepts, and familiarity with Big Data techniques
• Curious mind to learn, explore and identify biggest customer opportunities
• Build strong relationships across both technical and business/product teams, earn trust with leadership
• Driven towards forming opinions and conclusions through data and experimentation, rather than anecdotes and hearsay
• Willingness to dive deep into the tech stack as well as hands-on coding
• Experience in building end to end ML models, across the ML lifecycle
• Strong communication and leadership presence
• Technical skills- hands on with scripting required, with knowledge or willingness to learn tools/softwares. Knowledge of R, SQL, Python, Statistical modeling, experience with AWS/Azure/GCP ML suite
• Experience in the following domains/industries preferred- SaaS, ecommerce, pricing or payments
• Bachelors/Masters in a technical or natural sciences domain from a top university

Responsibilities

• Identify $ opportunities - think big picture, work with product, tech and customer-facing teams to identify the largest customer problems that can be solved using ML. Build business cases through a combination of market research and internal analytics
• Stakeholder relationships and strong communication - work closely with a wide variety of stakeholders to build cohesive plans and execute them. Influence senior leadership through a data-driven approach, including but not limited to market research, customer case studies and pilots/experimentation
• Technical expertise, simplify complexity - build end to end ML models, be it classification/ unsupervised/ LLMs using a combination of structured and unstructured data. Work with upstream data engineering and software engineering teams to procure, process and transform data into meaningful features
• End to end ownership, delivering results - Take models into production and maintain them through effective ML engineering, demonstrate tangible business value, and deliver solutions rather than products

Benefits

• Competitive compensation, corporate bonus program and performance rewards, company equity and retirement programs
• Medical insurance
• Generous, flexible time off
• Paid holidays, “wellness” days and company wide end of year break
• 6 months fully paid parental leave
• Learning & Development stipend
• Opportunities to volunteer and give back, including charitable donation match
• Free resources and support for your mental wellbeing