Description

Automattic, a globally distributed company behind influential platforms like WordPress, WooCommerce, and Tumblr, is seeking a highly skilled and impactful Senior Data Scientist to lead cross-functional data initiatives.

In this pivotal role, you will be a key driver of data-informed decision-making for our sophisticated products that empower publishing, commerce, and messaging for millions worldwide. You will collaborate closely with Product, Growth, Engineering, Design, and Business teams to uncover critical insights, shape strategic direction, and ultimately enhance the user experience across our diverse ecosystem.

As a valued member of our centralized data science team, you will be responsible for developing and implementing advanced data models, designing and executing rigorous experiments, and conducting in-depth analyses. Working in partnership with embedded analysts and engineers within various business units, you will translate complex data into actionable strategies that deliver tangible customer and business impact.

This position demands strong analytical expertise, a solid understanding of SaaS business models, and the ability to distill intricate data into clear and strategic recommendations for both technical and non-technical audiences. Furthermore, you will contribute to shaping the technical direction of our data science efforts, provide strategic guidance on execution, and champion the quality of data science and analytics initiatives throughout the company.

Primary Responsibilities

• Advanced Quantitative Analysis: Employ deep technical expertise in quantitative analysis, advanced statistical methods, rigorous experimentation, and sophisticated data mining techniques to develop data-driven strategies for our core publishing and commerce products.
• Proactive Opportunity Identification & Testing: Proactively identify, define, and rigorously test opportunities and key levers to enhance the product experience and drive growth, ensuring data-driven decision-making that yields measurable business and customer impact. Translate complex analytical insights into clear and actionable recommendations that directly influence product roadmaps and strategic investments.
• Advanced Model Development & Implementation: Contribute to the development and implementation of advanced data analysis techniques and sophisticated statistical models across multiple diverse business units.
• Company-Wide Data Strategy: Design and drive impactful company-wide data initiatives, playing a key role in shaping the overall direction of data analytics and insights to directly support critical strategic decisions at the highest levels of the organization.
• Mentorship & Guidance: Mentor and provide guidance to other data scientists and analysts within the team and across the organization.
• Strategic Partnerships: Partner closely with Growth, Product, Engineering, Design, and senior leadership to inform, influence, and effectively execute product and growth strategies, leveraging key data-driven insights to drive measurable and significant company-wide impact.
• Executive-Level Communication: Communicate complex strategic insights and data-backed recommendations clearly and concisely to non-technical stakeholders, including senior leadership, facilitating data-driven decision-making at the highest levels of the company.

Technical Requirements

• Extensive Data Science Experience: 5+ years of demonstrable experience in data science, analytics, or a closely related role within a technology company, preferably within a SaaS environment. A proven track record of working with large-scale, complex, product-focused datasets to drive measurable business impact is essential.
• Statistical & ML Expertise: Strong expertise in the principles and application of experimentation methodologies, a wide range of statistical analysis techniques (e.g., hypothesis testing, t-tests, regression analysis, time series analysis, bootstrapping), machine learning algorithms, and predictive modeling techniques.
• Python Proficiency: High proficiency in Python and key data science libraries, including Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn for data manipulation, analysis, and visualization.
• Distributed SQL Fluency: Fluency in using distributed SQL query engines such as Hive, Presto, or Trino for efficient querying and analysis of large datasets.
• Big Data Familiarity: Familiarity with big data technologies and frameworks (e.g., Hadoop, Spark) for processing and analyzing large-scale data.

Note: If you feel strongly that you have what it takes for this role but don’t check 100% of the boxes—that’s okay—we encourage you to apply anyway and highlight what you can bring to the table.