Lead Data Scientist

Job Title: Lead Data Scientist

Location: San Mateo County, CA (Onsite)

Job Summary

Own end-to-end delivery for a portfolio of data science and data engineering projects.

Lead a team of approximately five data science and data engineering practitioners.

Serve as the senior technical and delivery point of contact for client stakeholders.

Set solution direction, ensure quality and timeliness, and help grow team capabilities.

Remain hands-on with data and code while driving strategy, delivery, and people leadership.

Key Responsibilities

Own scoping, planning, and execution of data science and data engineering workstreams.

Ensure on-time, high-quality delivery against client commitments.

Lead, mentor, and develop a team of data scientists and data engineers.

Allocate work, review deliverables, and support career growth.

Serve as the primary technical liaison to client and partner stakeholders, including acquirer-facing and merchant-facing teams.

Translate business goals into analytical solutions and communicate results to technical and non-technical audiences.

Architect end-to-end solutions spanning data ingestion, pipelines, modeling, evaluation, and deployment across large-scale financial datasets.

Write and review production-grade Python and SQL code.

Establish engineering standards for reproducibility, testing, and code quality.

Guide the development of statistical and machine learning models, including segmentation, propensity modeling, forecasting, and anomaly/risk signal detection.

Ensure compliance with data privacy, security, and governance requirements for regulated financial data.

Contribute to estimation, staffing, and proposal activities.

Identify opportunities to expand engagement scope and impact.

Required Skills

Python with expert-level, production experience for data science and engineering.

Experience with pandas, scikit-learn, and standard machine learning/data science tooling.

Advanced SQL skills, including performance-aware query design for large relational and analytical datasets.

Demonstrated ownership of end-to-end project delivery from problem definition through deployment with measurable business outcomes.

Experience leading or mentoring teams and managing stakeholder commitments.

Strong stakeholder communication and presentation skills.

Ability to explain complex technical concepts to a variety of audiences.

Preferred Skills

Hands-on AWS experience with data and machine learning workloads, including services such as S3, Glue, EMR, Redshift, SageMaker, or equivalent.

Direct experience within the payments ecosystem, including issuers, acquirers, payment networks, or merchants.

Familiarity with transaction-level financial data.

Experience with modern data engineering practices, including orchestration, data modeling, CI/CD, and distributed processing frameworks such as Spark.

Exposure to MLOps, feature stores, and production model monitoring.

Prior consulting or client-facing delivery experience.

Qualifications

6+ years of experience delivering data science projects within financial institutions, including banking, payments, cards, lending, or other regulated environments.

Bachelor s or Master s degree in Computer Science, Statistics, Engineering, Mathematics, or a related quantitative field, or equivalent practical 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.

_RighttoWorkPoster.pdf