Job Description

Please note, to be eligible for this role you must be based in Berlin and hold the right to work in Germany.

This role will work on the exciting Zendesk AI Agent (Ultimate) product.

Ultimate were acquired by Zendesk in March 2024, we’ve become even more powerful.

Together with Zendesk we’re joining forces to build the world’s most advanced AI agents in CX.

THE ROLE:

We are looking for a Lead Data Analyst for our Analytics Core team here at Zendesk AI Agents.

This role in our newly created team will play a crucial role to build the foundation for  future analytics and insight capabilities for our product.  You will play a crucial role in identifying new ways to measure performance and key drivers, specifically in the context of generative bots, and enabling customers to continuously enhance the automation experience. 

Additionally, you will work with Data Analysts and Data Engineers to define data requirements for our analytics platform and assist product squads in creating effective tracking and measurement plans to ensure the impact of new features align with our product strategy. 

Key Responsibilities:

Advanced Analytics & Modelling:

• Building analytical solutions to support strategic product initiatives.
• Partner with product manager to identify product opportunities to apply advanced analytics to validate data product ideas.
• Collaborate with the product leadership and other stakeholders to develop actionable dashboards to measure product performance.

Strategic Data Leadership:

• Collaborate with leadership and engineering teams to define the long-term data and analytics strategy, aligning it with business goals.
• Champion data-driven decision making across the organization.

Data Architecture & Infrastructure:

• Work with data engineers to define data models and data requirements and  ensure efficient data pipelines. 

Collaboration & Knowledge Transfer:

• Collaborate with Analysts from various teams across the organization to facilitate effective communication and knowledge sharing between Data Science and Data Analysis functions.
• Mentor and support data analysts in their professional development, particularly in areas of advanced analytics and data modelling.

This role requires a strong blend of technical expertise and business acumen. You'll be an effective communicator who can bridge the gap between product , analytics, data science and engineering teams.

The ideal candidate for this role will have a deep understanding of the following:

Technical Skills:

• Working with large datasets and databases using SQL: Proficiency in data cleaning, transformation, and preparation for analytics. 
• Programming Languages: Proficiency in Python (or similar) for data manipulation and analysis.
• Machine Learning & Statistics: Knowledge of machine learning algorithms and their practical implementations. 
• Data Modeling & Management: Expertise in relational and non-relational databases, data modeling techniques, understanding of dbt and data quality management practices.
• Data Architecture & Infrastructure: Understanding of data warehousing, data lakes, big data technologies. 
• You have a Master’s degree in computer science, machine learning, statistics, engineering, mathematics or a related field.

Non-Technical Skills:

• Communication & Collaboration: Excellent communication skills to collaborate effectively with data analysts, engineers, and business stakeholders. Ability to translate complex data insights into actionable recommendations.
• Leadership & Mentorship: Strong leadership skills to guide data governance implementation and mentor data analysts in their professional development.
• Data Governance & Compliance: Knowledge of data governance frameworks (e.g., Data Management Body of Knowledge - DAMA) and relevant data privacy regulations (e.g., GDPR, CCPA).

How we measure success for this role, involves but not limited to:

• Increased adoption of data-driven decision making within the R&D teams.
• Increase in data quality metrics (accuracy, completeness, consistency).
• Positive feedback from stakeholders on the data scientist's leadership and contributions.

The Interview Process:

We want to be transparent about what you can expect from our interview process.

• Initial Call with Talent Team - 15 mins
• Hiring Manager Interview - 45 mins
• Take Home Challenge 
• Technical Interview - 1 hour
• Final interview with Leadership - 30 mins

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.

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 peopleandplaces@zendesk.com with your specific accommodation request.