Remote Data Scientist 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 key player in shaping the future of commerce, you will have opportunities to work across the suite of Zuora products and beyond, using AI to build, improve and optimize.

Requirements

• 5+ years of experience in the data science/machine learning domain, preferably with hands-on end-to-end model building experience
• 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. Always work backwards from the customer, to identify the simplest feasible solutions that can add maximum value
• 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