As an Applied Scientist, you will help design and build intelligent systems that turn data, machine learning, and LLMs into measurable business impact. You will work across the full lifecycle of applied AI problems — from identifying opportunities and formulating hypotheses, to developing models and evaluation frameworks, and iterating based on real-world outcomes.
You will partner closely with cross-functional stakeholders to understand user needs, define success criteria, and translate complex technical approaches into actionable insights. Your work will sit at the intersection of science, product, and engineering, with a strong focus on delivering high-impact solutions that improve customer experience and business performance.
Own business-relevant metrics such as churn reduction, AI attach rate, and seller productivity, and use data and scientific thinking to identify opportunities for improvement
Develop a deep understanding of users, their workflows, and pain points, and use those insights to inform what should be built next
Define hypotheses, success criteria, and evaluation approaches for AI and ML systems
Design, build, and evaluate LLM-powered applications, including agents, RAG systems, text-to-SQL solutions, and recommendation engines
Establish robust feedback loops for intelligent systems by instrumenting, measuring, and learning from user and business outcomes
Partner with engineers to move prototypes into production, ensuring scientific rigor and practical usability
Build and maintain Python-based services and APIs that support AI-driven applications
Collaborate on the data infrastructure that powers AI products, including Snowflake, dbt, and Airflow
Communicate findings, trade-offs, and recommendations clearly to both technical and non-technical stakeholders
Stay current with advances in LLMs, agent architectures, evaluation frameworks, and AI-assisted development workflows
Education & Experience
3+ years of experience in Data Science, Machine Learning, Applied Science, or a related field
BA/BS in Computer Science, Data Science, Statistics, Mathematics, or a related discipline
Advanced degree is highly preferred
Business Acumen & User Focus
Experience owning business outcomes through intelligent systems
Ability to identify high-impact opportunities and form informed opinions on what to build next
Strong user focus: you talk to users, understand their workflows, and let those insights guide your technical decisions
Deep understanding of the data insights action workflow and how to measure whether systems are driving outcomes
Track record of building trusted partnerships with business stakeholders
Technical Expertise
Hands-on experience building and evaluating ML or LLM-powered applications
Strong understanding of experimental design, evaluation frameworks, and model performance measurement
Experience with agent architectures, prompt engineering, or similar applied AI techniques
Strong Python programming skills for scientific experimentation and production-oriented implementation
Strong SQL skills and experience with cloud data warehouses
Familiarity with backend API design and modern web application concepts
Nice to have: experience with Snowflake, dbt, Airflow, or similar data infrastructure tools
Nice to have: experience with AI-assisted development workflows such as Claude Code, Cursor, Copilot, or similar
Nice to have: experience with frontend technologies and UX design, particularly React
Communication & Collaboration
Ability to clearly explain scientific concepts, trade-offs, and recommendations to technical and non-technical audiences
Experience working cross-functionally with engineers, analysts, product leaders, and business stakeholders
Strong collaboration skills and a continuous learning mindset
Opportunity to work at the intersection of applied science, AI, and software engineering
A chance to shape intelligent, LLM-powered products with measurable business impact
An environment that values experimentation, ownership, and continuous improvement
The opportunity to work on high-visibility, high-impact projects with strong cross-functional collaboration
The intelligent heart of customer experience
Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love.
Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week.
As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law.
Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster global diversity, equity, & inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here .
Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to [email protected] with your specific accommodation request.
