Role Description We're looking for a Marketing Data Scientist to join Figma's Data Science team and drive how we measure and optimize the impact of our global brand investments. In this role, you'll partner closely with Brand Marketing, Creative, Media, and Research teams to develop measurement frameworks, generate actionable insights, and influence strategic decisions that support long-term business growth. This is a unique opportunity to be the first dedicated Data Scientist supporting Brand Marketing at Figma. You'll work directly with senior marketing leaders to establish new measurement capabilities, solve complex business problems, and define the future of brand analytics at one of the world's most recognized software companies. This is a full time role that can be held from one of our US hubs or remotely in the United States. What you'll do at Figma: - Develop and own end-to-end measurement frameworks, attribution models, and channel-level evaluation tools to assess the impact of Figma's marketing investments across the full funnel and inform budget allocation. - Partner with stakeholders across Brand Marketing, Email, Lifecycle, Demand Gen and Research teams to define success metrics, uncover insights, and drive data-informed decision making. - Develop and apply statistical and machine learning models to solve key marketing challenges, including audience targeting, creative effectiveness, customer engagement, and campaign performance measurement. - Build dashboards, reporting frameworks, and analytical tools that help stakeholders understand brand performance and business impact. - Translate complex analyses into clear recommendations for marketing leaders and executive stakeholders. - Improve data quality, measurement infrastructure, and reporting capabilities to support a growing marketing organization — establishing standards and processes that scale with the business. - Proactively surface new opportunities to improve marketing effectiveness — from audience targeting to spend optimization — and bring data-backed recommendations to senior marketing and business planning discussions. Qualifications - 5+ years of experience in Data Science or Marketing Analytics, with a track record of supporting Marketing teams and measuring the impact of large-scale brand investments. - Strong foundation in statistics, experimentation, causal inference, and working with survey or qualitative research data. - Advanced proficiency in SQL and experience using Python, R, or similar tools to conduct analysis and build scalable measurement solutions. - Proven ability to influence senior non-technical leaders and cross-functional teams by translating complex analyses into clear, actionable recommendations. Requirements - Experience with media mix modeling (MMM) or multi-touch attribution (MTA) methodologies (not required but preferred). - Hands-on experience with marketing data platforms such as Segment, Amplitude, or similar tools. - Experience working in a B2B SaaS or PLG environment. Benefits - Equity to employees. - Competitive package of additional benefits, including health, dental & vision. - Retirement with company contribution. - Parental leave & reproductive or family planning support. - Mental health & wellness benefits. - Generous PTO and company recharge days. - Learning & development stipend. - Work from home stipend. - Cell phone reimbursement. - Sales incentive pay for most sales roles and an annual bonus plan for eligible non-sales roles.

Role Description As a Data Scientist on our Risk Team, your role is crucial in developing and optimizing machine learning models to detect and prevent fraud. You will be a key player in analyzing data, building predictive models, and implementing robust data-driven strategies to enhance our risk management processes. - Bridge the gap between theoretical data science and practical, scalable solutions in the fintech sector, focusing on risk assessment and mitigation. - Handle large-scale datasets, extract meaningful insights, and develop sophisticated algorithms to protect our ecosystem. Qualifications - Fluency in Python and SQL. - Proficient in ML libraries like Scikit, PyTorch, TensorFlow, etc. - Experience with cloud-based services like the Google Cloud platform. - Solid Data Visualization skills to create charts and dashboards. - Strong analytical skills, with attention to detail and accuracy. - Detail-oriented with a strong research mindset. - Ability to communicate effectively with multiple teams. - Ability to communicate and debate in English and Portuguese. Requirements - As a member of a fully remote and distributed team, you are expected to complete tasks autonomously, being highly collaborative and self-driven. - Curiosity of a child with the responsibility of a grown-up. Nice-to-have skills - Experience with the financial or payment industry. - Knowledge of distributed systems and parallel computing. - Understanding of DevOps practices, including continuous integration, continuous deployment, and containerization. Recruiting Process Outline - Online technical assessment. - Technical interview. - Cultural interview. Benefits - If you are not willing to do an online-quiz, please do not apply.

• Analyze and Assess Risk: Conduct in-depth analysis of financial data, transaction patterns, and user behavior to identify and assess potential credit, fraud, and compliance risks. • Develop and Implement Risk Controls: Partner with product, engineering and data science teams to design, build, and deploy automated risk controls and decisioning systems that balance user experience with platform safety. • Contribute to Strategic Planning: Provide valuable insights and recommendations to leadership on risk trends, policy improvements, and long-term risk strategy to support Found's growth and expansion. • Optimize Processes: Proactively identify areas for improvement in existing risk management processes and workflows, and drive initiatives to increase efficiency and scalability.

Role Description At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Data Annotation Specialists to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own - Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. - Labeling elements of a piece of content rather than the content as a whole. - Assigning predefined categories or labels to items. - Evaluating the perceived quality and/or appropriateness of content. - Generating labels to advance understanding of a concept, trend etc. - Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. - Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. - Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. - Ordering or ranking items based on a set of preferences or criteria. - Creating prompts or questions that will be used to generate responses from a language model or other AI system. - Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). - Generating responses to prompts or questions using a language model or other AI system. - Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. - Producing concise summaries of longer pieces of text or data. - Converting spoken language or audio content into written text. - Converting text or spoken language from one language to another. - Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. Qualifications - A High School Diploma or higher is required. - Professional or Expert level proficiency (C1/C2) in English. Requirements - The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Company Description Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.