Staff Data Scientist (Growth & Optimization)

Coursera was launched in 2012 by two Stanford Computer Science professors, Andrew Ng and Daphne Koller, with a mission to provide universal access to world-class learning. It is now one of the largest online learning platforms in the world, with 129 million registered learners as of June 30, 2023.

Coursera partners with over 300 leading university and industry partners to offer a broad catalog of content and credentials, including courses, Specializations, Professional Certificates, Guided Projects, and bachelor’s and master’s degrees. Institutions around the world use Coursera to upskill and reskill their employees, citizens, and students in fields such as data science, technology, and business. Coursera became a B Corp in February 2021.

Join us in our mission to create a world where anyone, anywhere can transform their life through access to education. We're seeking talented individuals who share our passion and drive to revolutionize the way the world learns.

We at Coursera are committed to building a globally diverse team and are thrilled to extend employment opportunities to individuals in any country where we have a legal entity. We require candidates to possess eligible working rights and have a compatible timezone overlap with their team to facilitate seamless collaboration. As a remote-first company, our interviews and onboarding are entirely virtual, providing a smooth and efficient experience for our candidates.

Job Overview:

We are seeking a skilled and agile Staff Data Scientist to join our Growth Science organization at Coursera, focusing on marketing and personalization initiatives. The candidate will be instrumental in driving hyper-personalized targeted marketing and growth for Coursera's business segments. A strong foundation in machine learning is expected, but the primary focus of this role will be leveraging data and insights for strategic decision-making, supported by a robust background in statistics, A/B testing, causal inference, and uplift modeling. The Staff Data Scientist will play an essential role in shaping the expansion of Coursera's marketing efforts through creative problem-solving, advanced analytics, interdisciplinary collaboration, and the ability to adapt quickly in a fast-paced growth environment.

Responsibilities:

Leverage data and advanced statistical techniques to develop data-driven marketing strategies, optimizing customer acquisition, engagement, and retention.Conduct comprehensive A/B testing, multivariate testing, causal inference, and uplift modeling to evaluate the effectiveness of marketing campaigns and facilitate data-driven decisions.Collaborate closely with cross-functional teams, including marketing, product, and engineering to optimize targeting techniques, ensuring accurate segmentation and tailored messaging.Develop and maintain dashboards and comprehensive reporting, providing actionable insights to stakeholders for informed strategy development.Implement and refine models for customer lifetime value, churn prediction, propensity scoring, and attribution analysis to target specific user groups and maximize business growth.Perform ad-hoc analytic requests and deep dive analysis of customer funnel data, presenting findings to leadership for data-informed decision-making and company strategy guidance.

Basic Qualifications:

• Master's or Bachelor's degree in Optimization, Operations Research, Statistics, Computer Science, or a closely related field.
• Demonstrated experience in marketing analytics, with a strong background in A/B testing, causal inference, multivariate testing, and uplift modeling.
• Prior experience in the marketing and optimization space, with a focus on LTV, overall revenue optimization, and cannibalization analysis.
• Proficient in using programming languages such as Python or R for statistical analysis and data manipulation as well as experience with SQL and data visualization tools like Tableau, Looker, or Power BI.
• Background in leveraging machine learning techniques for data-driven marketing and personalization with a solid understanding of customer segmentation methodologies and a proven track record of optimizing targeted campaigns.

Preferred Qualifications:

• Experience in building and maintaining data pipelines and ETL processes.
• Familiarity with marketing analytics tools such as Amplitude.Strong storytelling skills, with the ability to translate complex data and insights into actionable recommendations and engaging visualizations.
• Excellent communication, collaboration, and project management skills, with experience working in cross-functional teams.
• Demonstrated ability to adapt and excel in a fast-paced, evolving growth environment, responding to ad-h