- Страна
- США
- Зарплата
- 185 000 $ – 215 000 $
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Senior Data Scientist
Отличная вакансия в быстрорастущем финтех-стартапе с прозрачной вилкой зарплаты и сильной командой из топовых компаний (Uber, Google, Meta). Роль предполагает высокую степень ответственности и возможность напрямую влиять на продукт.
Сложность вакансии
Роль требует глубоких знаний в области статистики, причинно-следственного вывода (causal inference) и опыта вывода моделей в продакшн. Высокая планка ожиданий обусловлена необходимостью работать в быстром темпе стартапа и напрямую влиять на финансовые показатели через ценообразование и управление рисками.
Анализ зарплаты
Предложенная зарплата ($185k - $215k) полностью соответствует рыночным стандартам для Senior Data Scientist в Пало-Альто, одном из самых дорогих и конкурентных регионов мира. Верхняя граница вилки даже немного превышает медиану для аналогичных позиций в стартапах серии C/D.
Сопроводительное письмо
I am writing to express my interest in the Senior Data Scientist position at Mudflap. With over 5 years of experience in building production-ready machine learning models and a strong background in risk and pricing analytics, I am excited about the opportunity to contribute to a fast-growing marketplace that serves the backbone of the U.S. economy. My expertise in Python, SQL, and causal inference aligns perfectly with your mission to build a data-driven engine for the trucking industry.
In my previous roles, I have successfully led end-to-end ML projects, from initial problem formulation to production deployment and A/B testing. I am particularly drawn to Mudflap’s focus on customer obsession and high-impact domains like Risk and Pricing. I am confident that my technical leadership and ability to translate complex data into actionable business strategies will help Mudflap continue its impressive growth and innovation in the fintech space.
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Описание вакансии
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.
About the RoleAt 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.
What You’ll Do
- 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
What We’re Looking For
- 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, growth/marketing, or product analytics preferred.
- Comfortable working in a fast-paced startup environment where collaboration and flexibility are essential.
Perks and Benefits (What we offer):
- Competitive salary and equity in a high-growth startup
- Multiple health benefit options
- Responsible Time Off
- 401(k) matching
- Opportunities and support for major career growth
- Annual Company offsite event (Mudfest!)
The salary range for this role is $185,000 - 215,000. This information reflects a base salary range for this position based on current market data, which may be subject to change as new market data becomes available. The candidate's skills, experience, and other relevant factors will determine the exact compensation.
Company Overview (Who we are):
Mudflap is on a mission to transform the trucking and logistics industry by leveling the playing field for owner operators and small fleets. Backed by top-tier venture investors, including QED, Matrix Partners, Commerce Ventures, NFX, and 500 Startups and included in the Forbes Fintech 50 list, Mudflap offers fleet fuel management solutions. Our core team hails from Disney, Uber, Procore, DoorDash, Google, Meta, Capital One, Affirm and Brex.
Here are the core values that we believe in and look for in new teammates:
- Be Customer Obsessed: We deeply understand customer needs and put our customers at the center of everything we do
- Make it Count: Act like an owner by focusing on the impact of your work
- Find a Way: Be a creative problem solver who pushes past roadblocks to win for our customers and our teammates
- Sweat the Details: We keep our standards high and achieve them by paying attention to every detail
- Be Curious: Use a growth mindset to question assumptions, take calculated risks and stretch the boundaries of what’s possible
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Навыки
- A/B Testing
- Python
- Machine Learning
- Experiment Design
- SQL
- Statistics
- Predictive Modeling
- Causal Inference
- Cohort Analysis
- Data Manipulation
Возможные вопросы на собеседовании
Проверка опыта работы с ключевым доменом вакансии (Risk).
Как бы вы спроектировали систему оценки кредитного риска для новых клиентов в условиях отсутствия исторической информации о них (проблема холодного старта)?
Оценка навыков в области ценообразования и эластичности.
Опишите ваш подход к моделированию ценовой эластичности. Как вы будете учитывать внешние факторы, такие как цены конкурентов или сезонность?
Проверка методологической строгости в экспериментах.
Расскажите о случае, когда результаты A/B теста были неоднозначными. Как вы принимали решение о внедрении или отмене фичи?
Оценка инженерных навыков и понимания жизненного цикла ML.
Как вы обеспечиваете мониторинг качества моделей в продакшене и как боретесь с деградацией данных (data drift)?
Проверка лидерских качеств и умения работать с бизнесом.
Как вы объясните нетехническому стейкхолдеру (например, финансовому директору), почему сложная модель «черного ящика» лучше простой линейной регрессии в данном бизнес-кейсе?
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- Страна
- США
- Зарплата
- 185 000 $ – 215 000 $