Lead Data Science

• Position: Lead Data Science
• Location: San Mateo, CA (Onsite)

• Key Responsibilities
• Lead the end-to-end delivery of data science and data engineering projects, ensuring high-quality outcomes and timely execution.
• Manage, mentor, and support a team of approximately five data scientists and data engineers.
• Partner with client stakeholders to understand business objectives and translate them into scalable analytical solutions.
• Design and implement end-to-end data and machine learning solutions, including data ingestion, transformation, model development, evaluation, and deployment.
• Develop and review production-quality Python and SQL code while establishing engineering best practices for testing, documentation, and code quality.
• Guide the development of statistical and machine learning models for business use cases such as customer segmentation, forecasting, fraud detection, propensity modeling, and risk analytics.
• Ensure adherence to data governance, security, privacy, and regulatory requirements applicable to financial data.
• Support solution estimation, resource planning, proposal development, and identification of new business opportunities.

• Required Qualifications
• Experience delivering data science solutions within banking, payments, financial services, lending, or other regulated industries.
• Expert-level proficiency in Python for data science and engineering using libraries such as pandas, scikit-learn, and related tools.
• Advanced SQL skills with experience working on large-scale analytical datasets and performance optimization.
• Demonstrated experience leading end-to-end analytics or machine learning projects from design through deployment.
• Experience leading or mentoring technical teams while managing project delivery and stakeholder expectations.
• Strong communication and presentation skills with the ability to engage technical and business stakeholders.
• Bachelor's or Master's degree in Computer Science, Statistics, Engineering, Mathematics, or a related quantitative discipline, or equivalent practical experience.

• Preferred Qualifications
• Hands-on experience with AWS services such as S3, Glue, EMR, Redshift, SageMaker, or similar cloud technologies.
• Experience within the payments ecosystem, including issuers, acquirers, payment networks, or merchants.
• Knowledge of modern data engineering practices including Spark, orchestration frameworks, data modeling, and CI/CD pipelines.
• Experience with MLOps, feature stores, and production model monitoring.
• Prior consulting or client-facing delivery experience.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law. https://www.e-verify.gov/sites/default/files/everify/posters/IER_RighttoWorkPoster.pdf