Applied ML Scientist — Revenue & Customer Insights

Zendesk; Polska; Hybrid; PLN 180,000 - 320,000; Full time

Benefits offered by this job

Hybrid work model

Global offices

Job summary

Zendesk is hiring an Applied ML Scientist to build customer-intelligence systems that connect signals to revenue outcomes. You will train models, design experiments, and ship insights as production systems used daily by the business.

You will own problems end-to-end from question formulation to deployment and monitoring, collaborating with AI/ML Engineers and Data Analysts in the Enterprise Data & Analytics team.

Qualifications

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

Responsibilities

• 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 and unstructured data
• Use LLMs and deep learning where appropriate
• Define and track model performance in production and iterate when needed
• Own models end-to-end from prototype through production deployment, monitoring and maintenance
• Partner with product and engineering to embed intelligence for decision making
• Translate model outputs into actionable insights for sales, success, and product teams
• Collaborate with stakeholders to identify high-leverage questions and prioritize work

Skills

Python

SQL

Snowflake

LLMs

Embeddings

Data pipelines

Airflow/DBT

Copilot/Claude Code

Education

BA/BS in CS/Statistics/Math

Advanced degrees welcomed

Tools

Snowflake

Airflow

dbt

Claude Code

Cursor

Copilot

Job description

Zendesk is hiring an Applied ML Scientist to build customer-intelligence systems that connect signals to revenue outcomes. You will train models, design experiments, and ship insights as production systems used daily by the business.

You will own problems end-to-end from question formulation to deployment and monitoring, collaborating with AI/ML Engineers and Data Analysts in the Enterprise Data & Analytics team.