Senior Data Scientist

Mudflap•Palo Alto, CA

9d•$185,000 - $215,000•Hybrid

About The Position

At Mudflap, we’re building a data-driven engine to power decisions across every part of our business. We’re looking for versatile Senior 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. Work Location: 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 two key domains—Risk and Pricing —so you can apply your skills where you’re most passionate: What You’ll Do Risk: 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. Pricing: Drive strategic pricing decisions with rigorous analytics and modeling. Build price and elasticity models, estimate willingness-to-pay, design and analyze pricing experiments (A/B and incrementality), and deliver actionable insights on revenue, margin, and churn—partnering with Product, Finance, and Revenue Ops to turn models into pricing actions.

Requirements

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.
Comfortable working in a fast-paced startup environment where collaboration and flexibility are essential.

Nice To Haves

Experience in at least one of the domains: risk, growth/marketing, or product analytics preferred.

Responsibilities

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