Trustly

Product Analyst

• Design, implement, and analyze A/B and multivariate tests to optimize product features and drive conversion across both EU and US markets.
• Develop and maintain scalable data models within our data warehouse (e.g., dbt) to create single sources of truth for core product metrics.
• Build and deploy machine learning classification models (e.g., fraud detection, user segmentation) to enhance product quality and performance.
• Partner with Product Managers in the EU and US to define KPIs, prioritize features, and measure the impact of product launches.
• Conduct deep-dive analyses on complex product areas, translating findings into clear, persuasive recommendations for product improvements.
• Create and maintain automated dashboards and reports that provide real-time visibility into product health and user behavior.
• Collaborate with Data Engineering to ensure data quality, accessibility, and the implementation of proper tracking for new features.
• Educate and mentor product and business stakeholders on data interpretation and experimentation best practices.

Staff Product Analyst

Engineering Manager

• Lead, coach, and support a team of engineers, enabling them to perform at their best while fostering a culture of collaboration, ownership, and continuous learning
• Drive successful delivery of the team’s commitments, ensuring alignment with domain objectives and product goals
• Work hands-on with lead developers and engineers to design, implement, and maintain scalable systems and solutions aligned with Trustly’s technical standards
• Work closely with the product manager to define and prioritise the team’s roadmap, balancing short-term goals with long-term vision
• Ensure your team’s systems operate reliably in production, with high performance, availability, and maintainability
• Recruit, onboard, and mentor engineers, creating an environment where they can grow and thrive
• Advocate for and implement best practices in agile methodologies, DevOps, and engineering processes to continuously improve team effectiveness

Financial Planning and Analysis

• Drive the commercial strategy and execution for acquiring key financial services clients
• Own the full sales cycle - from lead generation and pitch to negotiation and contract closure
• Build and manage a strong, scalable pipeline aligned with business objectives and market trends
• Act as the primary contact for senior stakeholders at financial institutions, ensuring top-tier service and strategic alignment
• Lead onboarding and early-stage integration of new clients, collaborating with technical and operational teams
• Ensure compliance with regulatory, KYC, and risk requirements throughout the sales process
• Provide client and market insights to product, marketing, and leadership teams to support innovation and growth
• Represent the company at industry events and forums, building visibility and driving thought leadership in the sector

Head of Sales – Financial Services

Analytics Engineer

• Data Architecture and Modeling: Design, develop, and maintain scalable and robust data models to support reporting, business intelligence, and data analytics.
• Data Visualization: Develop and maintain insightful dashboards using Amazon QuickSight.
• Optimization and Automation: Identify and implement opportunities to improve efficiency, performance, and accuracy of current processes.
• Collaboration: Work closely with stakeholders to gather their business requirements and translate them into scalable data solutions.
• Data Quality and Governance: Establish and enforce best practices for data quality, documentation, and governance.
• Drive data literacy and adoption: Champion a data-driven culture within the organization by sharing knowledge, best practices, and promoting the use of data in decision-making.

Senior Data Insights Engineer

Customer Support

• Help to define and drive the evolution of our digital experiences for the services organization
• Encompass external support sites, content, bots, communities, SEO, and future technologies
• Leverage AI/ML capabilities to enhance and evolve customer experiences
• Evaluate the technology stack supporting digital experiences and recommend platform investments
• Define user stories and acceptance criteria to execute against the roadmap
• Manage dependencies effectively and ensure high-value delivery
• Provide hands-on support to configure or troubleshoot platforms when needed
• Apply a data-driven mindset to define KPIs for each platform
• Collaborate cross-functionally with teams to align and deliver best-in-class customer experiences

Digital Customer Experience Lead

Data Scientist

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A Trustly é líder em soluções de Open Banking, oferecendo um portfólio coeso de produtos financeiros e de pagamentos projetados para modernizar os pagamentos, reduzir custos e mitigar riscos. A empresa foca em disponibilizar pagamentos seguros e de baixo custo e serviços financeiros sem fricção por meio de conectividade líder no setor, oferecendo serviços como payouts instantâneos, onboarding de clientes, avaliação de risco e verificação de conta em tempo real. 

A Trustly atende a diversos setores, incluindo billers (empresas de cobrança), e-commerce, serviços financeiros e gaming, aproveitando dados financeiros de alta qualidade validados por bancos para aprimorar a experiência do usuário. Suas soluções são adaptadas às necessidades de grandes empresas (enterprise), com o objetivo de aumentar as taxas de aprovação, minimizar os custos de processamento e prevenir o risco de fraude. 

- funcionários

Fundada em 2008

💳 Fintech

💸 Finanças

🛍️ Comércio Eletrônico

Senior Data Scientist

2 minutos atrás

🇧🇷 Brasil – Remoto

⏰ Tempo Integral

🟠 Sênior

📊 Cientista de Dados

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Descrição

• Develop new novel and state of the art AI/machine learning models to support risk strategies;
• Recommend data-driven, risk-based business decisions to positively impact KPIs across Trustly's payment portfolio;
• Conduct analysis to measure model performance, compare performance across multiple models, and influence model strategy and selection decisions;
• Collaborate with ML Engineers to deploy AI/ML models and strategies in Trustly's decision engine;
• Explore raw source data, feature research and engineering, supporting decision capabilities;
• Support development and maintenance of risk modeling infrastructure, working closely with ML Engineers and ML Ops;
• Develop data and business-driven risk prevention rules and strategies;
• Monitor risk and decisions trends and performances, provide ongoing optimization adjustments as needed.

🎯 Requisitos

• University degree in mathematics, statistics, data science or another comparable field of study;
• Experience with Data Science/Machine Learning and AI;
• Experience developing statistical/machine learning/AI models and experiments;
• Risk experience in financial services, fintech or similar industry;
• Advanced skills in Python and SQL – Spark and Javascript also nice to have;
• Understanding of feature engineering and model development life cycle;
• Must have solid English skills to be able to communicate with English-speaking business stakeholders;

🏖️ Benefícios

• Bradesco health and dental plan, for you and your dependents, with no co-payment cost;
• Life insurance with differentiated coverage;
• Meal voucher and supermarket voucher;
• Home Office Allowance;
• Wellhub - Platform that gives access to spaces for physical activities and online classes;
• Trustly Club - Discount at educational institutions and partner stores;
• English Program - Online group classes with a private teacher;
• Extended maternity and paternity leave;
• Birthday Off;
• Flexible hours/Home Office - our culture is remote-first! You can work in every city in Brazil;
• Welcome Kit - We work with Apple equipment (Macbook Pro, iPhone) and we send many more treats! Spoiler alert: Equipment can be purchased by you according to internal criteria!;
• Annual premium - As a member of our team, you are eligible to receive an annual bonus, at the company's discretion, based on the achievement of our KPIs and individual performance;
• Referral Program - If you refer a candidate and we hire the person, you will receive a reward for that!

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Senior Data Scientist

People Operations

• Act as the subject matter expert for all HR systems
• Drive system improvements, integrations, and automations to improve efficiency and accuracy
• Partner with HR, Payroll, and IT teams to manage system configurations, permissions, and workflows
• Support the implementation and roll-out of new tools or system modules
• Create and maintain reports and dashboards to support People analytics and compliance
• Train People team members and managers on system usage and best practices
• Ensure data integrity and support audits through regular system maintenance and checks
• Lead or support change management and communication efforts related to systems and processes

People Systems Partner

Data Engineer

• At Trustly: mission to deliver a better way to pay and get paid; making Pay by Bank the new standard at checkout; connecting merchants and consumers globally.
• Work-from-anywhere policy allows employees in Brazil, the U.S., and Canada to work remotely within their country of residence; remote-first culture in Brazil.
• About the team: The DataOps team ensures data from applications, APIs, and tools is delivered in a secure, scalable, and structured way across multiple environments; works with batch (Airflow) and streaming (Kafka) pipelines; maintains platforms like Redshift and QuickSight; enables analytics and supports Data Science.
• Design, implement, and maintain the scalable data platform infrastructure (AWS, Kubernetes, EMR, Redshift, Glue, etc.).
• Manage and evolve client-faced tools and frameworks for data processing (e.g., QuickSight, Redshift Editor, Athena IDE, Metabase).
• Build and maintain secure, automated CI/CD pipelines for data components and infrastructure-as-code.
• Collaborate with DevOps and Security teams to ensure compliance, reliability, and scalability of the data platform.
• Provide development environments, standardized workflows, and tooling (e.g., Sagemaker Studio, Athena IDE, Redshift Editor, etc.) to improve developer experience.
• Support version control, release workflows, and automation for data transformation, jobs, data workloads and integrations used by data producers and consumers.
• Ensure high availability and performance of data tools through observability and alerting integrations.
• Implement data quality and validation checks (e.g., dbt tests, unit tests).
• Contribute to maintaining data catalogs and documentation for lineage and governance.
• Investigate and resolve issues in data pipelines, workloads, and integrations to ensure SLAs are met.
• Documentation of data flows, architectural setup and data model.

DataOps Engineer, Data Tools

Support Engineer

• Trustly is a Pay by Bank fintech connecting merchants and consumers across banks and countries.
• Provide Tier 2 technical services to merchants and internal teams (investigation and resolution of queries, real-time merchant technical escalations, developer support).
• Manage incidents proactively and reactively following ITIL best practices and support Post Incident Reviews (PIR).
• Perform advanced technical support including log analysis, diagnostics, debugging, and RESTful API troubleshooting.
• Escalate to Tier 3 (Engineering and SRE) for support requests and incidents, and test/validate bug fixes.
• Create and maintain issue logs, knowledge base articles, internal tools, and documentation; provide internal training and customer communication as needed.
• Participate in on-call rotation and external notifications and change management.