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Tech Lead Manager, Machine Learning, and Marketing

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Chime Enterprise
Full Time position
Listed on 2026-10-15
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
Salary/Wage Range or Industry Benchmark: 199000 - 275000 USD Yearly USD 199000.00 275000.00 YEAR
Job Description & How to Apply Below
Position: Tech Lead Manager, Machine Learning, Growth and Marketing New
Tech Lead Manager, Machine Learning, Growth and Marketing

San Francisco, CA, USA

About the Role

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 Tech Lead 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.

As a Tech Lead 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.

In this role, you can expect to
  • 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.
  • Drive strategic direction for ML initiatives in marketing, engagement, and growth by identifying opportunities where AI/ML can optimize our customer funnel.
  • 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.
  • Collaborate cross‑functionally with marketing, product, growth, and engineering teams to align machine learning initiatives with business objectives.
  • Leverage transactional and behavioral data to enhance customer targeting, optimize acquisition spend, and improve retention strategies.
  • Establish ML best practices, including model development, validation, deployment, and monitoring, ensuring scalability and business impact.
  • Advocate for a data‑driven culture, partnering with business leaders to drive strategic decisions through experimentation and predictive analytics.
  • Stay ahead of industry trends, bringing cutting‑edge AI/ML techniques into our marketing and growth strategies.
To thrive in this role, you have
  • 7+ years of experience developing machine learning models for marketing and growth, from inception to production, with a focus on customer acquisition, engagement, and retention.
  • 5+ years of experience leading data science teams, with a proven track record of mentoring, coaching, and driving impactful machine learning solutions.
  • Strong expertise in marketing and growth analytics, including experience with customer segmentation, LTV modeling, churn prediction, referral systems, and multi‑touch attribution.
  • Deep understanding of AI/ML techniques, including classification, clustering, reinforcement learning, optimization, deep learning, and NLP for customer engagement.
  • Hands‑on experience deploying machine learning models in real‑world production environments, integrating with marketing tech stacks and growth platforms.
  • Strong product intuition with the ability to work iteratively in a fast‑paced, cross‑functional environment.
  • M.S. or Ph.D. in Machine Learning, Computer Science, Statistics, or a related STEM field.
  • Proficiency in Python and SQL, with experience in building ML pipelines and wrangling large‑scale data.
  • Experience with modern ML and data engineering technologies, such as AWS, Kafka, Airflow, Redis, MySQL, Postgres, Spark,…
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