Sr. Staff Product Data Scientist

We're Celonis, the global leader in Process Mining technology and one of the world's fastest-growing SaaS firms. We believe there is a massive opportunity to unlock productivity by placing data and intelligence at the core of business processes - and for that, we need you to join us.

The Team:

The Product Analytics & Data Sciences team, a part of the Product & Engineering organization, empowers teams across the company to make evidence-based decisions. We deliver actionable insights by collecting, organizing and interpreting data about user journeys, product telemetry, incidents, infrastructure utilization, sales motions, and much more. We transform data into analytic assets by conducting exploratory analysis, identifying outliers, validating hypotheses, building statistical models, quantifying risk; communicating findings through well crafted stories and critical recommendations. .

The Role:

As a Sr. Staff Product Data Scientist, you'll be a pivotal leader within our Product Analytics & Data Sciences team, directly influencing critical decision-making in a hyper-growth environment. You'll own the end-to-end process of transforming data into significant value, leveraging your advanced analytical and data science expertise to oversee the development of robust data pipelines, sophisticated machine learning models, and compelling visualizations. Beyond your technical leadership, you'll be instrumental in fostering a data-driven culture, leading complex stakeholder discussions, and delivering impactful insights to engineers, managers, and executives through masterful storytelling. This role demands not only exceptional data expertise but also the ability to build and mentor a high-performing team, set long-term data science strategies, and champion innovative approaches to product analytics.

The work you’ll do:

• Perform a hands-on leadership role, serving as the organization's primary data science authority. You will guide the team in generating data-driven insights, translating complex information into strategic findings and actionable recommendations for product and engineering leadership. Essential skills include translating quantitative insights into compelling visualizations and narratives for high-level discussions and cross-functional organizational alignment.
• Work closely with various departments (e.g. Engineering, Product Management, Value Engineering, Marketing, Sales) to understand their data needs, translate business problems into analytical solutions, leading by example, and ensure the insights generated are actionable and integrated into decision-making processes across the organization.
• Leveraging sophisticated statistical analysis and advanced modeling techniques across diverse datasets, including product telemetry, incident logs, user journeys, sales, and infrastructure utilization. This effort aims to boost product adoption, enhance features, and improve customer satisfaction, all while optimizing resource utilization.
• Contributing to the development and evolution of the company's data infrastructure, tools, and methodologies. This could involve evaluating new technologies, refining data engineering processes, establishing best practices for data governance and quality, and ensuring the data science team has the necessary resources and platforms to operate effectively and scale their impact.
• Stay at the forefront of data science innovation and help define the organizational vision and strategic roadmap for analytics. You will also provide critical mentorship and technical leadership to data scientists and analytics engineers, fostering their growth and enhancing the data science function's technical prowess.

The qualifications you need:

• Advanced Degree: Bachelors degree or equivalent with a strong focus on Mathematics, Computer Science, Data Science, or a related quantitative field. Masters or PhD preferred. 
• Extensive Experience: 15+ years of relevant experience, with at least 6+ years as a Staff Product Analytics Engineer / Staff Product Data Scientist or similar, demonstrating a proven track record of partnering effectively with product, engineering, and growth teams at a senior level.
• Technical Mastery: Expert-level technical competence with advanced analytical tools for data extraction, visualization, and analysis (e.g., advanced SQL, Python with extensive libraries like Pandas, NumPy, Scikit-learn, PySpark).
• Deep Statistical and Machine Learning Expertise: In-depth understanding and practical application of advanced statistical techniques, experimental design, and various machine learning methodologies for complex product challenges.
• Big Data and Predictive Modeling Leadership: De