Applied Machine Learning Scientist

Zendesk, Inc.; Portugal; Híbrido; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

Zendesk, Inc. is seeking an Applied Machine Learning Scientist to build models that predict revenue-related outcomes and surface actionable insights.

You will train, validate, and deploy end-to-end ML solutions in collaboration with AI/ML Engineers, Data Engineers, and Analysts within Enterprise Data & Analytics. You will own the modeling lifecycle—from problem formulation to deployment and monitoring—delivering measurable business impact while handling both structured and unstructured data and

Formación

• 3–5 years in Applied ML, Data Science or related quantitative field with measurable business impact.
• Experience training models on messy real-world data with label noise, data drift and robust validation.
• Experience applying ML to structured and unstructured data including NLP, embeddings, LLMs or deep learning.
• Production-grade engineering skills: Python, SQL, software engineering best practices, deployment and monitoring of ML models.

Responsabilidades

• Design, train, evaluate, and deploy ML models predicting/revealing revenue outcomes (churn, expansion, conversion, engagement).
• Build end-to-end ML systems from data prep to production deployment and monitoring.
• Develop insights from structured and unstructured data using statistical modelling, NLP, embeddings, LLMs, and deep learning.
• Design experiments to link customer behavior and product usage to business outcomes, translating model outputs into actions.
• Collaborate with Product, Engineering, and stakeholders to identify high-impact ML opportunities.
• Monitor model performance, detect drift, validate outcomes, and iterate based on real-world feedback.

Conocimientos

Python

SQL

ML deployment

Experiment design

Data analysis

NLP

LLMs

Deep learning

Statistics

Product mindset

Herramientas

Docker

ML pipelines

Descripción del empleo

Job Description

The Enterprise Machine Learning team drives organizational value through scalable ML solutions and data-driven insights, fundamentally changing how business decisions are made. We collaborate closely with stakeholders, applying the latest advances in machine learning and statistical modeling to create highly impactful outcomes. Our commitment is to advance the state of applied science and robust system design to enhance and expand our core business capabilities.

Job Description

The Enterprise Machine Learning team drives organizational value through scalable ML solutions and data-driven insights, fundamentally changing how business decisions are made. We collaborate closely with stakeholders, applying the latest advances in machine learning and statistical modeling to create highly impactful outcomes. Our commitment is to advance the state of applied science and robust system design to enhance and expand our core business capabilities.

Role Overview

We've spent the past year consolidating and validating our revenue data, most signals now live in one place. The next step is building a customer intelligence layer: systems that dynamically learn which signals drive outcomes, adapt as the business evolves, and surface insights that change how we act.

As an Applied Machine Learning Scientist, you will be the person who makes that happen. You will train models, design experiments, and uncover the patterns that connect customer behavior to revenue outcomes. Then ship those insights as production systems that the business relies on daily. You own problems end-to-end: from formulating the right question, to training and validating models, to deploying them and measuring whether they actually moved the needle, in a closed feedback loop.

You will work alongside a team of AI/ML Engineers, Data Engineers, and Analysts as part of the Enterprise Data & Analytics department. Your focus is the science: understanding what drives outcomes, building models that learn from data, and turning that understanding into systems that work.

Key Responsibilities

• Design, train, evaluate, and deploy machine learning models that predict and explain revenue-related outcomes, including churn, expansion, conversion, and customer engagement.
• Build and own end-to-end ML systems, from data preparation and experimentation through production deployment, continuous retraining, monitoring, and performance optimization.
• Develop intelligence from structured and unstructured data, applying statistical modelling, modern NLP, embeddings, LLMs, and deep learning where they create measurable business value.
• Design and run experiments to uncover the relationships between customer behavior, product usage, and business outcomes, translating model outputs into actionable insights.
• Partner closely with Product, Engineering, and business stakeholders to identify high-impact opportunities, prioritize ML initiatives, and embed intelligence into decision-making workflows.
• Measure and maximize business impact by monitoring model performance, detecting drift, validating outcomes, and continuously iterating based on real-world results and feedback.

This Role Is For You If…

• You have 3–5 years of experience in Applied Machine Learning, Data Science, or a related quantitative field, with a track record of building models that deliver measurable business impact.
• You bring foundation in machine learning and statistics, with hands‑on experience training models on messy, real‑world data. You're comfortable dealing with label noise, class imbalance, feature leakage, data drift, and designing robust validation strategies.
• You are experienced in applying ML to both structured and unstructured data, including modern NLP techniques, embeddings, LLMs, or deep learning where they create meaningful business value.
• You have production‑grade engineering skills, including Python, SQL, software engineering best practices, and experience deploying, monitoring, and maintaining ML models.
• You have pragmatic, product‑oriented mindset. You get more satisfaction from shipping a simple model that improves a business metric than building a complex one with marginally better offline performance. You think in terms of business outcomes, user behavior, and measurable impact—not model sophistication alone.
• You proactively identify high‑impact opportunities, form opinions based on data and user understanding, and continuously iterate on your work.

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 [e-mail] with your specific accommodation request.