Zendesk

Applied Machine Learning Scientist

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MidZdalnie·LisbonFull-time

#441748·Dodano miesiąc temu·4

Źródło: Zendesk

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Tech Stack / Keywords

LLM Python SQL Snowflake AirflowdbtA/B testingMachine LearningStatistical ModelingDeep Learning

Firma i stanowisko

Zendesk software powers billions of customer service conversations globally. The role is part of the Enterprise Machine Learning team within the Enterprise Data & Analytics department, focusing on applying machine learning and statistical modeling to drive business decisions and outcomes.

Wymagania

3–5 years' experience in applied machine learning, data science, or related field
BA/BS in Computer Science, Statistics, Mathematics, or a related quantitative discipline; advanced degrees welcomed
Strong foundations in statistical modeling and machine learning methods such as regression, classification, survival analysis, causal inference, and uplift modeling
Experience training models on real-world datasets with feature engineering and validation strategies
Experience working with unstructured data using embeddings, fine-tuning, or learned representations, understanding LLMs as modeling tools
Strong production-grade Python programming skills, including tests and clean abstractions
Strong SQL skills and experience with cloud data warehouses, preferably Snowflake
Experience deploying and monitoring models in production (batch or real-time)

Nice to have:

Experience with experiment design, A/B testing, and causal inference
Experience with orchestration tools such as Airflow or dbt
Experience with AI-assisted development workflows like Claude Code, Cursor, or Copilot

Obowiązki

Train, evaluate, and deploy models to predict and explain revenue-related outcomes such as churn, expansion, and engagement
Design and run experiments to link customer signals with business results
Build production ML pipelines for continuous learning, retraining, validation, and scalable prediction serving
Work with large volumes of structured and unstructured data, including support tickets and product feedback
Use LLMs and deep learning techniques like embeddings, fine-tuning, and text feature extraction
Define and track model performance, monitor drift, and measure business impact
Own models end-to-end from prototype through production deployment and maintenance
Partner with product and engineering teams to embed intelligence in user decision-making
Translate model outputs into actionable insights for sales, success, and product teams
Collaborate with stakeholders to prioritize modeling work based on business impact

Inne informacje

Artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications. Zendesk is an equal opportunity employer committed to global diversity, equity, & inclusion. Reasonable accommodations are made for applicants with disabilities.

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