The 'Zendesk Analytics Prototyping' (ZAP) team is seeking a Staff Data Scientist to drive our mission of measuring and optimizing the impact of our AI features. In this role, you will design and build advanced measurement frameworks, develop statistical models, and refine descriptive analytics to provide actionable insights that directly influence operational performance. If you're passionate about leveraging data science to uncover the true ROI of innovative AI capabilities like Agent Copilot, we want to hear from you.
What you'll be doing:
1. Develop descriptive analytics frameworks that track foundational AI metrics (e.g. usage, deflection success, resolution efficiency) to monitor and report on the ongoing performance of AI features.
2. Develop statistical models to estimate the ROI of AI features by identifying key success drivers and quantifying improvements in operational performance.
3. Develop cohort segmentation research to offer a robust framework for performance benchmarking.
4. Work closely with cross-functional teams including Engineering, Product, Sales/GTM, and Analytics to align data science research strategies with business goals.
5. Contribute to the analytics vision of the team and bring innovative data science solutions to complex challenges.
What you bring to the role:
Basic Qualifications:
1. 7+ years of experience in data science, with a proven track record of building predictive models, classification algorithms, and advanced analytics frameworks.
2. Bachelor's or Master's degree in Data Science, Statistics, Economics, or a related quantitative field or equivalent experience.
3. Strong proficiency in SQL.
4. Strong proficiency in statistical analysis and causal inference methodologies, with hands-on experience using tools such as Python or R.
5. Solid understanding of data visualization tools and techniques to communicate complex findings to both technical and non-technical audiences.
6. Excellent problem-solving, analytical, and communication skills, with the ability to collaborate effectively across teams.
Preferred Qualifications:
1. PhD in Data Science, Statistics, Economics, or a related quantitative field.
2. Experience in the AI or machine learning domain, specifically related to evaluating the impact of AI features.
3. Expertise in developing measurement and benchmarking frameworks that directly drive business insights.
4. Familiarity with big data technologies and cloud-based data platforms (e.g. Snowflake, DBT, AirFlow).
5. Demonstrated experience with A/B testing, experimental design, and statistical modeling in large-scale environments.
6. Prior exposure to CRM or customer support data environments is a plus.
Our Data and Tech Stack:
ELT & Data Orchestration: Snowflake, dbt, Airflow, Kafka
Machine Learning & Analytics: Python/R, PyTorch, TensorFlow, AWS Batch and EMR for ML pipelines
Hybrid: In this role, our hybrid experience is designed at the team level to give you a rich onsite experience packed with connection, collaboration, learning, and celebration - while also giving you flexibility to work remotely for part of the week. This role must attend our local office for part of the week. The specific in-office schedule is to be determined by the hiring manager.
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