Come Make an Impact on Millions of Brazilians! At RecargaPay, we’re on a mission to deliver the best payment experience for Brazilian consumers and small businesses — by building a powerful digital ecosystem where the banked and unbanked connect, and where consumers and merchants have a one-stop shop for all their financial needs. We serve over 10 million users and process more than USD 4 billion annually. We’ve been profitable since 2022 and operate our own credit business. We are an AI-first, 100% remote team, scaling in the rapidly changing Brazilian financial market. Our goal? Deliver the best payment experience in Brazil for people and small businesses alike. We value autonomy, ownership, and a bias for action. We’re looking for people who are curious, hands-on, and driven by impact — who want to solve real problems, work with strong teams, and rethink what’s possible. If you’re ready to do your best work, at scale, with purpose — this is your place. Position Overview Do you want to challenge the limits of data science in a high-impact, growing environment? At RecargaPay, we are looking for a Specialist Data Scientist to join our Data Science team, with the mission of supporting the development, monitoring, and evolution of credit models and decision strategies. As a Specialist Data Scientist, you will be responsible for leading the development and implementation of advanced machine learning models and analytical solutions to solve complex credit and transaction risk challenges. You will be part of the Data Science team, focusing on technical leadership, mentoring, and the adoption of new technologies. Key Responsibilities - Develop and implement real-time scoring models to quantify the risk level of transactions and credit operations. - Build predictive models using internal and third-party data to optimize user onboarding and reduce losses. - Evolve static rule engines into dynamic, graph-based ones, enabling more intelligent and adaptable rule management. - Lead the adoption of new technologies like Databricks and Data Catalogue, advocating for best practices and facilitating a transition to a more modern and efficient data environment. - Analyze large volumes of transactional, user behavior, and demographic data to identify patterns, trends, and opportunities for improvement in risk assessment. - Develop and implement fingerprinting and geographic tracking solutions to improve risk assessment. - Guide and mentor team members, sharing your experience and knowledge, and leading key projects from a technical perspective. - Monitor and analyze the performance of credit models, focusing on their stability and accuracy.

Title: Scientist II - Molecular and Proteomic Immunology Location: Seattle United States Job Description: Scientist II Molecular and Proteomic Immunology The mission of the Allen Institute is to unlock the complexities of bioscience and advance our knowledge to improve human health. Using an open science, multi-scale, team-oriented approach, the Allen Institute focuses on accelerating foundational research, developing standards and models, and cultivating new ideas to make a broad, transformational impact on science. The mission of the Allen Institute for Immunology is to advance the fundamental understanding of human immunology through the study of immune health and diseases where excessive or impaired immune responses drive pathological processes. The Institute will employ a multi-disciplinary team approach in collaboration with academic centers of human immunology to generate novel mechanistic insights into the immune synapse in health and in diseases such as autoimmunity or oncology. The Institute will simultaneously provide a foundational data set and tools for future immunological research as well as a novel collaboration portal for the broader scientific community. The Allen Institute for Immunology is looking for an exceptional molecular immunologist (Scientist II) to join a team focused on using and developing molecular and/or proteomic approaches to comprehensively study the interactions of the immune system. Specific responsibilities will include the design and development of new assays, technologies, and in vitro and ex vivo immunologic studies along with the analysis and synthesis of data generated through our cellular, molecular and proteomic platforms or their derivatives. A flexible and creative mindset along with the ability to function in a team to bring projects to completion on a timeline is essential. The successful candidate will have a strong background in molecular and/or proteomic methodologies along with prior neuroscience and/or immunology experience. Strongest consideration will be given to candidates with a proven track record in identifying and progressing novel hypotheses forward in discovery research and technology development. This position is expected to last through December 2028 based on business needs and funding. At the Allen Institute, we believe that science is for everyone and should be open to everyone. We are dedicated to combating biases and reducing barriers to STEM careers more broadly. We also believe that science is better when it includes different perspectives and voices. We strive to make the Allen Institute a place where everyone feels like they belong and are empowered to do their best work in a supportive environment. We are an equal-opportunity employer and strongly encourage people from all backgrounds to apply for our open positions. Essential Functions - Support the development and application of molecular and proteomic technologies to drive biological insight in the context of immunology. Examples include spatial and droplet based NGS platforms such as Xenium and 10x FLEX or REFLEX - Development of cellular engineering approaches for dissecting immune function. Examples could include molecular recorder systems and high throughput screens - Design, execute and analyze in vitro and ex vivo immunological studies utilizing cell lines, primary cells, and tissues to develop and test hypothesis, possibly including the utilization of genetic mouse models - Collaboration with a team to bring projects to completion on a timeline Note: Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This description reflects managements assignment of essential functions; it does not proscribe or restrict the tasks that may be assigned. Required Education and Experience - Ph.D. or equivalent combination of degree and experience in a life sciences discipline - 3+ years of postdoctoral experience Preferred Education and Experience - A strong background in molecular biology including NGS platforms - Experience in cellular immunology - Direct experience with advanced approaches in deconstructing immunologic mechanisms & testing hypotheses (e.g. targeted mutagenesis using CRISPR/Cas9, phenotypic screening, antibody-based immune modulation, lentiviral work, cell culture, etc.) - Proven success in troubleshooting and innovation on existing platforms, including publications and/or patents - Demonstrated ability to independently analyze data through coding languages (R, python, bash, version control) - Exceptional oral and written communication skills and ability to effectively present complicated concepts internally and externally in a cross-discipline environment Work Environment - Working in a laboratory environment with potential exposure to lasers, biohazards Physical Demands - Occasional lifting to 30 pounds - Fine motor movements in fingers/hands to operate computers and other office equipment; repetitive motion with lab equipment - Stooping, bending, crouching Position Type/Expected Hours of Work - May need to work outside of standard working hours at times - This role is currently working onsite and is expected to work onsite for the majority of working hours. The primary work location for this role is 615 Westlake Ave N., with flexibility to work remotely on a limited basis. We are a Washington State employer; any remote work must be performed in Washington State. - This position is expected to last through December 2028, based on business needs and funding Additional Eligibility Qualifications - All employees who work with live animals must complete an Occupational Health medical history form and/or consultation with an Occupational Health Provider and receive clearance to work with animals. Depending on your health history and job responsibilities, an annual respiratory health screening and clearance to use a respirator may also be required. Additional Comments - Please note, this opportunity may offer work visa sponsorship - Please note, this opportunity may offer relocation assistance Annualized Salary Range - $105,600 - $130,650 * - Final salary depends on required education for the role, experience, and level of skills relevant to the role, along with work location, where applicable. Benefits - Employees (and their families) are eligible to enroll in benefits per eligibility rules outlined in the Allen Institutes Benefits Guide. These benefits include medical, dental, vision, and basic life insurance. Employees are also eligible to enroll in the Allen Institutes 401k plan. Paid time off is also available as outlined in the Allen Institutes Benefits Guide. Details on the Allen Institutes benefits offering are located at the following link to the Benefits Guide:

• This role is unique in that it directly improves the safety, trust, and quality of real-world user experiences by advancing Airbnb’s ability to understand, interpret and act on content at scale. • You will help shape how the platform reasons about listings, profiles, messages and other user-generated content by building the next generation of Trust Content Understanding Models. • Advance Airbnb’s content integrity capabilities by building Natural Language Processing (NLP) and LLM-based models that understand intent, policy compliance, quality and risk across listings, profiles, and user communications. • Develop high-performing models for detecting problematic or misleading content, including text classification, semantic similarity, information extraction and generative model-based reasoning for policy interpretation and enforcement. • Design and optimize human-in-the-loop Machine Learning (ML) systems for content review, labeling, escalation and continuous model improvement. • Build systems to detect emerging content risks and abuse patterns across regions, cohorts and surfaces using statistical, ML and representation-learning approaches. • Design intelligent sampling and evaluation strategies to measure rare events, policy recall, false positives/negatives and model blind spots in large-scale content systems. • Build and deploy production AI/ML systems for content integrity and trust content understanding, including feature engineering, model development and evaluation, thresholding, error analysis and end-to-end model lifecycle management. • Partner with inference data scientists to conduct rigorous quantitative analyses, applying working knowledge of causal inference to interpret results, assess impact, and identify gaps and opportunities to improve content quality and trust outcomes. • Develop frameworks to analyze tradeoffs between enforcement accuracy, user experience, operational cost and coverage, and propose strategies to optimize overall system effectiveness. • Deliver robust research reports with effective data visualizations, clear storytelling and bullet-proof accuracy to drive forward impact in collaboration with cross-functional partners in product, engineering and operations. • Think strategically about how to scale and evolve Airbnb’s content integrity defenses, helping define the long-term vision for the role of AI-driven content understanding across the Trust ecosystem.

Role Description We are looking for a Senior Data Scientist to join our GeoData team. You will drive architectural decisions, ensure high performance and reliability, mentor engineers, and work closely with product and backend teams to deliver scalable solutions from discovery to release. Key Responsibilities - Lead the entire machine learning model lifecycle, from initial research and hypothesis testing to production deployment and maintenance. - Translate complex business goals into well-defined data science problems and quantifiable metrics. - Design and develop robust, scalable machine learning systems from scratch, including data analysis, annotation, and processing pipelines. - Contribute to the overall system architecture and integrate ML models with existing backend services and infrastructure. - Monitor and maintain deployed models, proactively identifying and addressing issues like concept drift to ensure consistent performance. - Support the development and growth of other team members through mentorship and participation in onboarding programs. - Drive continuous improvement by automating repetitive tasks and proposing innovative solutions that lead to significant business impact. - Communicate complex technical concepts and findings clearly and concisely to both technical and non-technical stakeholders. Qualifications - Previous experience in a data science or machine learning role. - An academic background in a quantitative field such as Computer Science, Mathematics, or a related discipline will be a plus. - Expert-level proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit-learn, PyTorch). - Deep expertise in classic machine learning and deep learning techniques, with a strong understanding of advanced mathematics relevant to these fields. - Experience with ML system design and MLOps practices for building, testing, deploying, and monitoring models in a production environment. - Proven experience with event systems, deployment environments, and maintaining production services. - Familiarity with technologies for streaming, batch, and async data processing. - Proficiency in at least one specialized ML domain (e.g., NLP, Computer Vision, Tabular ML, Graph Neural Networks). - Strong understanding of software system design principles and the ability to contribute to architectural discussions. - Experience in experimental design to validate hypotheses and measure the effectiveness of solutions. - A solid grasp of security, risk, and control concepts in a production environment. Benefits - Stable salary, official employment. - Health insurance. - Remote work and flexible schedule. - Access to professional counseling services including psychological, financial, and legal support. - Discount club membership. - Diverse internal training programs. - Partially or fully paid additional training courses. - All necessary work equipment.