Senior​/Data Scientist

Mudflap serves the $800B trucking industry, the backbone of the U.S. economy. Our market-leading payment products help truckers save thousands of dollars on fuel (their #1 business expense), while providing our fuel stop partners with access to new, hard-to-reach customers. We’re a fast-growing marketplace business looking for a new customer-obsessed teammate to join us on this exciting journey.

At Mudflap, we’re building a data-driven engine to power decisions across every part of our business. We’re looking for versatile Senior and Staff level Data Scientists to join our small, high-impact analytics and ML team. You’ll work closely with product, engineering, operations, and cross-functional partners to build data products, ML models, run experiments, and deliver insights that directly influence our growth and product strategy.

This role is based in Palo Alto, CA and involves a hybrid work approach, balancing in-office collaboration with the ability to work remotely.

To support our team, we offer:

• Commuter benefits to ease your travel

• Lunches and snacks to keep you fueled

• A collaborative, high-growth environment where you’ll work closely with talented teammates across the company

We’re hiring for three key domains—
Product, Risk and Growth —so you can apply your skills where you’re most passionate:

Drive strategic product decisions through advanced analytics and experimentation. Design and execute A/B tests, build predictive models, and develop data-driven insights that directly impact product roadmaps and business outcomes. Partner closely with product managers, engineers, and leadership to identify opportunities, measure feature success, and optimize user experiences.

Identify, model, and mitigate credit and fraud risks across our platform. Build and strengthen our underwriting capabilities for credit risk, and develop predictive models to reduce fraud losses. Partner with Product, engineering and operations teams to implement scalable risk strategies.

Drive strategic growth insights through robust data architecture and advanced analytics. Lead the design and implementation of scalable data pipelines, attribution models, and measurement frameworks that power marketing optimization across channels. Own end-to-end data infrastructure including customer journey tracking, incrementality testing platforms, and real-time reporting systems.

• Drive strategic data science initiatives that directly impact business outcomes, working closely with executive leadership to identify high-value opportunities in your domain.

• Lead end-to-end machine learning projects from problem formulation through production deployment, including model development, validation, A/B testing, and performance monitoring. solve high-impact business problems such as fraudulent risk assessment, underwriting, customer segmentation, etc.

• Drive data-driven decision making across cross-functional partnerships — Collaborate closely with Product, Engineering, Ops, Risk teams, etc. to translate complex business requirements into analytical solutions and communicate insights to executive stakeholders

• Mentor junior data scientists and analysts and establish best practices — Provide technical leadership, code reviews, and strategic guidance while developing scalable data science methodologies and standards across the organization

• Lead experimentation strategy and drive product innovation — Own end-to-end A/B testing frameworks, mentor teams on experimental design, and translate test results into actionable product improvements that directly impact key business metrics

• 5+ years of experience in data science, analytics, or related fields.

• Proficiency in SQL and Python for data manipulation, modeling, and automation.

• Experience building production-ready models and pipelines.

• Strong statistical knowledge and experience designing experiments (A/B testing, cohort analysis, causal inference).

• Excellent communication skills—ability to present complex insights clearly to technical and non-technical stakeholders.

• Experience in at least one of the domains: risk,…