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Senior Data Science Manager-Unsecured Lending Underwriting

Оценка ИИ

Привлекательная позиция в топовой финтех-компании с возможностью влиять на ключевые бизнес-показатели и работать с передовым стеком технологий. Высокие требования компенсируются масштабом задач и профессиональным окружением.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена необходимостью сочетать глубокие технические знания в области ML (LLM, Deep Learning) с жесткими регуляторными требованиями банковского сектора (SR 11-7) и управленческим опытом.

Анализ зарплаты

Медиана240 000 $
Рынок195 000 $ – 290 000 $
Оценка ИИ

Указанная позиция Senior Manager в Сан-Франциско предполагает уровень компенсации выше среднего по рынку США для сферы Data Science. Рыночные оценки для аналогичных ролей в финтехе колеблются от 200 до 280 тысяч долларов базового оклада, не включая бонусы и опционы.

Сопроводительное письмо

I am writing to express my strong interest in the Senior Data Science Manager position for Unsecured Lending Underwriting at SoFi. With over 8 years of experience in credit risk modeling and a proven track record of leading high-performing technical teams, I am confident in my ability to drive the next generation of underwriting capabilities. My background includes extensive work with advanced machine learning techniques and a deep understanding of SR 11-7 standards, which aligns perfectly with SoFi’s commitment to innovation within a regulated framework.

In my previous roles, I have successfully transitioned traditional modeling functions toward modern MLOps environments, leveraging alternative data sources to improve predictive accuracy while reducing losses. I am particularly drawn to SoFi’s mission of helping members reach their financial goals through mobile-first technology. I look forward to the opportunity to bring my expertise in NLP, Deep Learning, and model governance to the Risk Data Science team and contribute to the continued success of your personal and student loan products.

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Присоединяйтесь к лидеру финтеха и возглавьте трансформацию систем кредитного андеррайтинга в SoFi!

Описание вакансии

Employee Applicant Privacy Notice

Who we are:

Shape a brighter financial future with us.

Together with our members, we’re changing the way people think about and interact with personal finance.

We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world.

The Role:

SoFi is seeking an inspirational and deeply experienced Senior Manager to lead the Unsecured Underwriting Data Science function in our Risk Data Science team. Reporting to the Head of Risk Data Science, this role will lead the development, deployment, and governance of credit decisioning models for Personal Loans and Student Loans.

The ideal candidate is a hands-on leader who can transition the team from traditional modeling to next-generation machine learning platforms, leveraging emerging data sources (e.g., cash flow, alternative bureaus) to significantly improve underwriting performance, reduce losses, and ensure rigorous adherence to Model Risk Management (MRM) standards. This role requires exceptional organizational leadership, an ability to influence stakeholders, and proven success in delivering complex models into a regulated production environment.

What You'll Do

  • Underwriting Excellence: Directly oversee the development and deployment of Next Generation Underwriting models designed to increase origination while maintaining loss guardrails.
  • Drive Next-Generation Capabilities: Incorporate industry trends and advanced techniques (NLP, Graph Mining, LLMs, Deep Learning) to solve complex, high-impact risk problems where established principles may not fully apply.
  • Alternative Data Strategy: Spearhead the evaluation and integration of alternative data sources (tri-bureau, LexisNexis, cash flow data) to enhance predictive power across all credit products.
  • Lead the current team of high-performing Staff and Senior Data Scientists. Recruit, mentor, and foster talent through deliberate interactions, succession planning, and creating a high-accountability, low-ego culture.
  • Model Risk Management (MRM): Act as the primary owner for all models in the portfolio, ensuring robust documentation, monitoring, and successfully navigating the 2nd Line of Defense (2LOD) review and approval process (SR 11-7 familiarity is mandatory).
  • Stakeholder Alignment: Interact and negotiate with senior management and external stakeholders to reconcile competing views and drive critical, high-impact business decisions.
  • Automation and Efficiency: Lead efforts to automate model monitoring and governance processes to create scalable and auditable infrastructure.

What You'll Need

  • Experience: 8+ years of progressive experience in credit risk, modeling, and data science within a regulated financial institution (FinTech, Bank, or similar), with at least 3 years in a people management role, managing technical staff.
  • Education: Master’s or Ph.D. degree in a quantitative field (Statistics, Computer Science, Engineering, Operations Research, etc.).
  • Technical Acumen: Deep expertise in advanced statistical and machine learning modeling techniques (e.g., Gradient Boosting, Deep Learning, Causal Inference).
  • Regulatory Knowledge: Detailed working knowledge of model risk management standards (e.g., SR 11-7) and the ability to operate within a highly regulated environment.
  • Tools & Platforms: Expert-level proficiency in Python (PySpark, scikit-learn, TensorFlow/PyTorch) and SQL/data warehouse technologies (e.g., Snowflake, Hive). Familiarity with modern MLOps platforms and cloud computing (AWS).
  • 3+ years of progressive people management experience is required, including the ability to recruit, mentor, and foster talent within a team of high-performing Staff and Senior Data Scientists.
  • Communication: Ability to distill highly complex analytical concepts into clear, concise, and compelling narratives for non-technical leadership.

Compensation and Benefits

The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate’s experience, skills, and location.

To view all of our comprehensive and competitive benefits, visit our Benefits at SoFi page!

SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
The Company hires the best qualified candidate for the job, without regard to protected characteristics.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
New York applicants: Notice of Employee Rights
SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.

Internal Employees

If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.

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Навыки

  • AWS
  • Python
  • PyTorch
  • Machine Learning
  • SQL
  • Statistics
  • Deep Learning
  • MLOps
  • NLP
  • Scikit-learn
  • Snowflake
  • PySpark
  • TensorFlow
  • Hive
  • Causal Inference

Возможные вопросы на собеседовании

Вакансия требует обязательного знания стандартов SR 11-7. Важно понять, как кандидат обеспечивает соответствие моделей требованиям регулятора.

Опишите ваш опыт прохождения проверок второй линии защиты (2LOD). С какими основными трудностями вы сталкивались при валидации сложных ML-моделей?

Роль предполагает переход от традиционных методов к современным ML-платформам.

Как бы вы организовали процесс миграции с традиционных логистических регрессий на градиентный бустинг или нейронные сети в контексте кредитного скоринга, сохраняя при этом интерпретируемость?

Упоминается использование альтернативных данных (cash flow, LexisNexis).

Каков ваш подход к оценке инкрементальной ценности (incremental lift) новых источников данных, таких как транзакционные данные о движении денежных средств?

Позиция требует управления штатом Senior и Staff специалистов.

Как вы подходите к менторству опытных Data Scientist-ов и разрешению технических конфликтов внутри команды при выборе архитектуры модели?

Вакансия подразумевает работу в финтехе, где важна скорость и автоматизация.

Расскажите о вашем опыте внедрения MLOps практик для автоматизации мониторинга производительности моделей и обнаружения дрейфа данных (data drift).

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