Jobs / United States / Chime Financial INC
Tech Lead Manager, Machine Learning, Growth and Marketing
Chime Financial INC · 🇺🇸 San Francisco, CA, USA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 81 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 20 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Chime Financial INC paid sponsored hires in similar roles4 certified filings for “Senior Project Manager, CRM” (Project Management Specialists) in CA: $170k–$195k, median $175k. Most were filed at wage level IV (75%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Chime Financial INC
The US Department of Labor certified 81 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 20 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Chime Financial INC →
About the role
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, Snowflake, Looker. • Exceptional communication and stakeholder