Applied ML Scientist: Revenue Outcomes & Production Models

Zendesk, Inc.; Lisboa; Híbrido; EUR 60 000 - 90 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid work model

Equal opportunity employer

Accommodations for disabled applicants

Resumo da oferta

Zendesk, Inc. is seeking an Applied ML Scientist to advance customer intelligence by building models that predict revenue outcomes and surface actionable insights.

You will own end-to-end process from problem framing to deployment and monitoring, collaborating with AI/ML Engineers, Data Engineers, and Analysts in the Enterprise Data & Analytics team. The role emphasizes production-grade Python, handling both structured and unstructured data, and leveraging embeddings/LLMs where beneficial to

Qualificações

• 3-5 years' experience in applied machine learning, data science, or a related field.
• BA/BS in Computer Science, Statistics, Mathematics, or related quantitative discipline.
• Advanced degrees welcome but not required.

Responsabilidades

• Train, evaluate, and deploy models that predict and explain revenue-related outcomes (churn, expansion, conversion, engagement).
• Design and run experiments to establish relationships between customer signals and business results.
• Build production ML pipelines that learn continuously: ingest new data, retrain, validate, and serve predictions at scale.
• Work with large volumes of structured data (usage metrics, revenue events, account attributes) and unstructured data (support tickets, conversations, product feedback).
• Use LLMs and deep learning where appropriate: embeddings, fine-tuning, text feature extraction.

Conhecimentos

Applied ML

Python

SQL

Snowflake

Production ML

Experiment design

Formação académica

BA/BS in CS/Statistics/Math

Advanced degree welcome

Ferramentas

Airflow

dbt

Claude Code

Cursor

Copilot

Descrição da oferta de emprego

Zendesk, Inc. is seeking an Applied ML Scientist to advance customer intelligence by building models that predict revenue outcomes and surface actionable insights.

You will own end-to-end process from problem framing to deployment and monitoring, collaborating with AI/ML Engineers, Data Engineers, and Analysts in the Enterprise Data & Analytics team. The role emphasizes production-grade Python, handling both structured and unstructured data, and leveraging embeddings/LLMs where beneficial to