Title: Senior Data Scientist I Location: Paris United States Full time Job Description: We're Checkout.com - you might not know our name, but companies like eBay, ASOS, Klarna, Uber Eats, and Sony do. That moment when you check out online? We make it happen. Checkout.com is where the world checks out. Our global network powers billions of transactions every year, making money move without making a fuss. We spent years perfecting a service most people will never notice. Because when digital payments just work, businesses grow, customers stay, and no one stops to think about why. With 19 offices spanning six continents, we feel at home everywhere - but London is our HQ. Wherever our people work their magic, they're fast-moving, performance-obsessed, and driven by being better every day. Ideal. Because a role here isn't just another job; it's a career-defining opportunity to build the future of fintech. Job Description About the role: As a Data Scientist at Checkout.com, you will be embedded within the Identity Verification Team, a critical function focused on building innovative products to verify the identities of individuals and businesses globally. In this high-impact role, you will be instrumental in the development of next-generation verification features, deploying intelligent, production-ready solutions by leveraging state-of-the-art Generative AI and Computer Vision technologies. You will be expected to work closely and collaboratively with Product, Development, and Data teams to ensure successful, end-to-end delivery of these solutions, while constantly researching and integrating emerging technologies. A core part of your contribution will be safeguarding data integrity and ensuring compliance, and translating complex data insights into clear, actionable recommendations for stakeholders to support informed, data-driven decision-making across Checkout.com. What you will be doing: - Drive the design and development of innovative GenAI and Computer Vision-based approaches to solve complex, real-world identity verification challenges. - Execute deep-dive exploratory data analysis (EDA) and technical discoveries to generate meaningful, novel insights that shape product direction. - Design, implement, and analyze rigorous experiments and A/B tests to quantitatively measure model performance and directly guide iterative improvements. - Take full ownership of new model development, managing the end-to-end lifecycle from initial conceptualization and design through to deployment and monitoring in a production environment. - Actively collaborate with cross-functional teams (Engineering, Product, Risk) across the company to maximize the positive impact of data science initiatives. - Champion a culture of technical excellence, cross-team learning, and knowledge sharing within the Data organization. About You: - Over 5 years of applied experience as a Data Scientist in a data-intensive environment, working with complex, large-scale, and diversified data sets. - Expert-level Python programming knowledge and demonstrable experience deploying models in a high-traffic production environment. - Proven experience in GenAI / Computer Vision model experimentation, including the creation and implementation of deep-learning models and scalable GenAI pipelines. - Exceptional communication skills, with the ability to articulate technical concepts and complex findings clearly to both technical and non-technical audiences. - A proactive mindset: the drive to challenge existing processes and decisions to continuously improve efficiency and outcomes for everyone. - Highly curious, able to take initiative, and work with a high degree of autonomy. - Strong commitment to a data-driven approach, consistently defining clear success metrics and rigorously measuring progress against them. - Flexible and adaptable, with a strong willingness to rapidly learn and master new technologies and domains. Bonus Points: - Solid theoretical and practical knowledge of Computer Vision, Machine Learning, and Generative AI principles. - Direct experience solving real-world business problems through innovative, data-driven approaches. Bring all of you to work We create the conditions for high performers to thrive - through real ownership, fewer blockers, and work that makes a difference from day one. Here, you'll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It's a place where ambition gets met with opportunity - and where your growth is in your hands. We work as one team, and we back each other to succeed. So whatever your background or identity, if you're ready to grow and make a difference, you'll be right at home here. It's important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. Curious about what it's like to be part of our team? Visit our Careers Page to learn more about our culture, open roles, and what drives us.

• Partner with our Product and Business Teams to understand their needs, translate them into data science solutions, and provide actionable insights. • Develop and implement data science solutions (ML models, GenAI products, hybrid approaches, data analytics) to optimize marketing and products strategies, enhance user experience and shape targeting. • Collaborate closely with cross-functional teams (e.g. other Data&AI teams, Technology teams) to ensure seamless integration of data-driven initiatives. • Stay ahead of the curve exploring cutting-edge methods and being on top of new trends in Data Science & AI. • Communicate insights and recommendations to the management and business teams, and other data community members. • Conduct end-to-end data products: exploring business needs (skills: understanding business, communication), analyze problems and propose thesis (data analytics), develop a solution (skills: hands-on ML/AI), present insights and results (skills: communication, translating technical stuff to non-technical people, ppt/BI), maintain the solution (skills: basic BI skills, model monitoring).

• Transform revenue data into AI-powered intelligence that drives smarter, faster, and more predictive decision-making across the business. • Lead the application of advanced analytics, machine learning, and generative AI to uncover patterns in sales performance, customer behavior, and revenue dynamics. • Build scalable predictive models and embed AI into revenue workflows to help forecast growth, reduce churn, optimize sales strategies, and identify high-value opportunities. • Directly influence executive decision-making, accelerate insight generation, and position AI as a core driver of measurable business impact across the revenue organization. • Conduct in-depth analysis of sales cycles, conversion rates, customer churn, and other revenue-driving activities using advanced AI-powered analytics tools and large-scale data processing techniques. • Leverage generative AI, machine learning platforms, and automated analytics solutions to accelerate insight generation and improve analytical depth and speed. • Translate complex, AI-derived data findings into clear, concise, and compelling narratives for various stakeholders. • Identify opportunities where AI can create measurable business impact and collaborate with stakeholders to define business problems and translate them into AI-powered data science solutions.

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. A culture of experimentation enables Netflix to continuously evolve and improve our products, delivering more joy to existing members and attracting new members from around the globe. Because experimentation is so pervasive at Netflix, we continually enable new capabilities and onboard new initiatives to the platform with close cross-functional collaboration with our Data Science partners. At the nerve center of experimentation at Netflix is our internal, Netflix-wide, Experimentation Platform, responsible for democratizing trustworthy experiments across the company and enabling new capabilities across the company. We are looking to expand the number of full-stack data science faculty on the team to better support experimentation best-practice and drive further innovation in data science tooling. Responsibilities: - Work closely with data science and engineering stakeholders to act as a strategic thought partner and onboard new workflows. - Design, build, operate, and maintain mathematics and engineering implementations of methodologies employed by the experimentation platform, as well as facilitating data science partner contributions. - Maintain existing inference related data and analysis pipelines, including compute clusters and API services. - Develop new tooling to meet emerging experimentation-related business needs. - Proactively work with the rest of the XP team (including other full-stack data scientists) to ensure that our platform continues to deliver trustworthy and useful analysis results. Qualifications: - Advanced degree (PhD or Masters) in Computer Science, Statistics, Economics, Applied Mathematics, or related quantitative field - 3+ years experience with statistics / inference, ideally in an experimentation context. - 3+ years experience with data science languages, ideally including Python and SQL. - 3+ years building and operating applications serving internal or external production traffic - Ability to translate mathematical concepts into clean maintainable engineering code. - Curiosity to learn new statistics, methods, optimization techniques, etc. - Excellent communication and collaboration skills. - Able to bring clarity and life to ambiguous problems. Curious to learn more about our experimentation culture at Netflix? Read up on experimentation culture at Netflix and browse the Netflix Research page. Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $372,000.00 - $600,000.00. This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here. Netflix is a unique culture and environment. Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.