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Data Science Manager

Оценка ИИ

Высокий балл за сильный бренд компании, современный стек технологий (GCP/Vertex AI) и отличный социальный пакет, включая опционы и гибкий график. Роль предлагает реальное влияние на продукт мирового уровня.


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Оценка ИИ

Роль требует сочетания сильных управленческих навыков (от 2 лет опыта) и глубокой технической экспертизы в GCP и Vertex AI. Кандидат должен быть готов работать «руками» с кодом, одновременно управляя стратегическим роадмапом в сложной финансовой домене.

Анализ зарплаты

Медиана82 000 €
Рынок70 000 € – 95 000 €
Оценка ИИ

Зарплата в объявлении не указана, но для позиции Data Science Manager в Лиссабоне рыночный диапазон обычно составляет от 70 000 до 95 000 евро в год. GoCardless как международный финтех-единорог обычно предлагает конкурентоспособные условия, часто находящиеся в верхней границе рынка, дополненные пакетом акций (equity).

Сопроводительное письмо

I am writing to express my strong interest in the Data Science Manager position at GoCardless. With a solid background in managing high-performing data science teams and a deep technical expertise in Python, SQL, and the GCP ecosystem, I am excited about the opportunity to lead the Payment Intelligence team in Lisbon. My experience in overseeing the full lifecycle of mission-critical ML models aligns perfectly with your mission to deliver intelligent payment solutions.

Throughout my career, I have focused on bridging the gap between complex technical architectures and strategic business value. I am particularly drawn to GoCardless's commitment to using AI-powered solutions for fraud prevention and payment optimization. I am confident that my hands-on leadership style and experience in navigating technical trade-offs will contribute significantly to your global payment network's success and the professional growth of the data science team.

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Присоединяйтесь к GoCardless, чтобы возглавить разработку инновационных ML-решений в сфере глобальных платежей!

Описание вакансии

About Us at GoCardless

GoCardless is a global bank payment company. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect and send payments through direct debit, real-time payments and open banking.

GoCardless processes US$130bn+ of payments annually, across 30+ countries; helping customers collect and send both recurring and one-off payments, without the chasing, stress or expensive fees. We use AI-powered solutions to improve payment success and reduce fraud. And, with open banking connectivity to over 2,500 banks, we help our customers make faster, more informed decisions.

We are headquartered in the UK with offices in London and Leeds, and additional locations in Australia, France, Ireland, Latvia, Portugal and the United States.

At GoCardless, we're all about supporting you! We’re committed to making our hiring process inclusive and accessible. If you need extra support or adjustments, reach out to your Talent Partner — we’re here to help!

And remember: we don’t expect you to meet every single requirement. If you’re excited by this role, we encourage you to apply!

The role

Data sits at the core of our mission. We leverage bank account data to deliver high-value, intelligent payment solutions for our customers, from enhancing payment success rates to driving payer fraud prevention.

As a Data Science Manager within our Payment Intelligence team, you’ll partner with Software Engineers, Product Managers, and Designers to turn big ideas into reality. You’ll own the full lifecycle of our algorithms, shaping everything from the initial concept to production-ready code that powers our global payment network.

At GoCardless, our stack is centered around Google Cloud Platform and Vertex AI, providing a high-performance environment for innovation. Our Data Scientists operate at the intersection of Python, SQL, and BigQuery to build and deploy high-performance models at scale.

What you’ll do

  • Manage and mentor a high-performing team of Data Scientists, fostering a culture of technical excellence and supporting their long-term career development.
  • Oversee the end-to-end lifecycle of mission-critical ML models that power real-time payment decisions.
  • Shape the strategic roadmap for the Payment Intelligence space, translating complex data challenges into actionable, high-impact goals.
  • Drive cross-functional impact by working closely across disciplines to build end-to-end technical solutions, from concept to production.
  • Influence Senior Leadership by acting as the bridge between technical complexity and business value, communicating ML strategy to senior stakeholders.

What excites you

  • Driving cutting-edge advancements in Data, AI, and Machine Learning within the payments space with a multidisciplinary team.
  • Mentoring a high-performing team and fostering a culture of technical excellence.
  • Solving the complex, real-time challenges of fraud prevention and payment optimisation at scale.
  • Building production-grade ML models on a streamlined GCP and Vertex AI stack to drive fintech innovation.

What excites us

  • 2+ years managing Data Scientists within complex, high-stakes domains.
  • A hands-on leader comfortable diving into the codebase. You bring strong expertise in Python and SQL to oversee the full lifecycle of a model, from initial prototype to robust production deployment.
  • A decisive collaborator who can navigate technical trade-offs and translate complex ML concepts for cross-functional stakeholders and leadership.
  • Familiarity with complex data environments and model architectures, such as deep learning (experience in Fintech, Fraud Prevention, or Payments is a big plus).

The Good Stuff!

  • Wellbeing: Dedicated support and medical cover to keep you healthy.
  • Work Away Scheme: Work from anywhere for up to 90 days in any 12-month period.
  • Hybrid Working: Our hybrid model offers flexibility, with in-office days determined by your team.
  • Equity: All permanently employed GeeCees get equity to share in our success.
  • Parental leave: Tailored leave to support your life's great adventure.
  • Time off: Annual holiday leave based on your location, supplemented by 3 volunteer days and 4 wellness days.

Life at GoCardless

We're an organisation defined by our values; We start with why before we begin any project, to ensure it’s aligned with our mission. We make it happen, working with urgency and taking personal accountability for getting things done. We act with integrity, always. We care deeply about what we do and we know it's essential that we be humble whilst we do it. Our Values form part of the GoCardless DNA, and are used to not only help us nurture and develop our culture, but to deliver impactful work that will help us to achieve our vision.

Diversity & Inclusion

We’re building the payment network of the future, and to achieve our goal, we need a diverse team with a range of perspectives and experiences. As of July 2024, here’s where we stand:

  • 45% identify as women
  • 23% identify as Black, Asian, Mixed, or Other
  • 10% identify as LGBTQIA+
  • 9% identify as neurodiverse
  • 2% identify as disabled

If you want to learn more, you can read about our Employee Resource Groups and objectives here as well as our latestD&I Report

Sustainability at GoCardless

We’re committed to reducing our environmental impact and leaving a sustainable world for future generations. As co-founders of the Tech Zero coalition, we’re working towards a climate-positive future. Check out our sustainabilityaction plan here.

Find out more about Life at GoCardless via X,Instagram andLinkedIn.

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Навыки

  • Python
  • SQL
  • Google Cloud Platform
  • Vertex AI
  • BigQuery
  • Machine Learning
  • Deep Learning
  • Fraud Prevention
  • Fintech

Возможные вопросы на собеседовании

Проверка опыта управления и развития талантов в команде.

Расскажите о случае, когда вы помогли члену вашей команды Data Science значительно вырасти профессионально или преодолеть серьезный технический вызов.

Оценка способности балансировать между качеством модели и бизнес-требованиями.

Как вы принимаете решение о компромиссе между точностью модели и скоростью её вывода в продакшн в условиях реального времени?

Проверка технического лидерства и опыта работы с современным стеком.

Опишите ваш опыт работы с Vertex AI или аналогичными платформами для управления полным жизненным циклом ML-моделей.

Оценка навыков коммуникации со стейкхолдерами.

Как вы объясняете сложные концепции машинного обучения (например, причины ложноположительных срабатываний в антифрод-системе) руководству, не имеющему технического бэкграунда?

Проверка доменных знаний в финтехе.

С какими специфическими проблемами данных вы сталкивались при разработке моделей для предотвращения мошенничества или оптимизации платежей?

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