Engineering Manager, Machine Learning - Growth and Marketing

<p><strong>About the Role</strong></p> <p>Chime’s Data Science and Machine Learning team is building models, services, and platforms that transform how millions of users manage and grow their financial lives. We are looking for a hands-on Engineering Manager with deep technical expertise in machine learning and data science, particularly within the Growth and Marketing domain. Beyond technical proficiency, we value creativity, user empathy, and strong collaboration.</p> <p>As a Engineering Manager within our Growth and Marketing team, you will lead a talented group of data scientists and machine learning engineers to develop innovative growth and marketing models. These models will provide critical insights into acquiring, retaining and growing Chime members, broaden access to credit, and ensure financial inclusivity. You will play a pivotal role in creating innovative, ground-up products while driving the development of cutting-edge acquisition and retention models and solutions. If you are passionate about marketing, growth, customer acquisition and retention models, this role could be a great fit for you.</p> <p>The base salary offered for this role and level of experience will begin at $211,000 and up to $275,000. Full-time employees are also eligible for a bonus, competitive equity package, and benefits. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.</p> <p><strong>In this role, you can expect to</strong></p> <ul> <li>Lead and inspire a high-performing team of data scientists and ML engineers, ensuring the successful development and deployment of machine learning solutions for customer acquisition, conversion and retention.</li> <li>Drive strategic direction for ML initiatives in marketing, engagement, and growth by identifying opportunities where AI/ML can optimize our customer funnel.</li> <li>Oversee the end-to-end development of machine learning models such as lifetime value prediction, churn risk modeling, customer segmentation, marketing attribution, referral recommendations, and personalized communications.</li> <li>Collaborate cross-functionally with marketing, product, growth, and engineering teams to align machine learning initiatives with business objectives.</li> <li>Leverage transactional and behavioral data to enhance customer targeting, optimize acquisition spend, and improve retention strategies.</li> <li>Establish ML best practices, including model development, validation, deployment, and monitoring, ensuring scalability and business impact.</li> <li>Advocate for a data-driven culture, partnering with business leaders to drive strategic decisions through experimentation and predictive analytics.</li> <li>Stay ahead of industry trends, bringing cutting-edge AI/ML techniques into our