About Airwallex Airwallex is the only unified payments and financial platform for global businesses. Powered by our unique combination of proprietary infrastructure and software, we empower over 200,000 businesses worldwide - including Brex, Rippling, Navan, Qantas, SHEIN and many more - with fully integrated solutions to manage everything from business accounts, payments, spend management and treasury, to embedded finance at a global scale. Proudly founded in Melbourne, we have a team of over 2,000 of the brightest and most innovative people in tech across 26 offices around the globe. Valued at US$8 billion and backed by world-leading investors including T. Rowe Price, Visa, Mastercard, Robinhood Ventures, Sequoia, Salesforce Ventures, DST Global, and Lone Pine Capital, Airwallex is leading the charge in building the global payments and financial platform of the future. If you're ready to do the most ambitious work of your career, join us. Attributes We Value We hire successful builders with founder-like energy who want real impact, accelerated learning, and true ownership. You bring strong role-related expertise and sharp thinking, and you're motivated by our mission and operating principles. You move fast with good judgment, dig deep with curiosity, and make decisions from first principles, balancing speed and rigor. You're humble and collaborative; turn zero-to-one ideas into real products, and you "get stuff done" end-to-end. You use AI to work smarter and solve problems faster. Here, you'll tackle complex, high-visibility problems with exceptional teammates and grow your career as we build the future of global banking. If that sounds like you, let's build what's next. About the team We're looking for talented Data Scientist who can push the boundaries of our existing models and help design state-of-the-art solutions to GTM challenges that accelerate revenue growth and improve commercial efficiency. In this role, you'll partner closely with Product, Growth, and Commercial teams to shape and build the next-generation data science foundation at Airwallex. This role is ideal for someone who takes meaningful ownership from day one-someone who digs deeply into data to understand why outcomes change (not just what changed), balancing analytical rigor with speed and business context-and then leverages AI to translate those insights into scalable models and solid data foundations. Learn more about the data science team in this blog. This role is based in Singapore. Responsibilities: - Translate complexity into action: Turn complex statistical and modeling results into clear, compelling, and actionable narratives for cross-functional partners and executive audiences. - Uncover and scale revenue insights: Lead proactive, exploratory analyses to identify latent revenue levers, emerging trends, and root causes behind shifts in key GTM metrics-and operationalize these learnings into repeatable workflows, automated pipelines, and scalable data science operating models. - Build revenue forecasting and performance insights: Develop and own revenue forecasting and forward-looking performance insights (e.g., pipeline health, conversion and retention drivers, scenario planning), providing a reliable "source of truth" that helps teams make faster, better commercial decisions. - Apply advanced causal inference: Use advanced observational causal inference methods (e.g., DiD, synthetic control, DoubleML) to estimate impact and inform decisions when randomized experiments are infeasible. - Embed AI into commercial workflows: Design and deploy AI-enabled solutions across the sales and customer lifecycle-enhancing sales calls and coaching, improving sales effectiveness, and generating proactive, transaction-based customer insights to drive retention and expansion. Who you are We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory. Minimum qualifications: - 7+ years of industry experience and an advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Engineering, Economics, or a related discipline). - Strong analytical intuition and structured problem-solving-you ask the right questions, explore data thoughtfully, and synthesize clear, defensible conclusions. - Excellent communicator and storyteller-able to translate technical work into crisp, actionable recommendations for both technical and non-technical stakeholders, including executives. - Deep curiosity about GTM performance and customer behavior-you go beyond "what happened" to understand "why it happened," while staying pragmatic and focused on impact. - Strong foundations in causal inference and forecasting, with experience applying methods such as DiD, synthetic control, and modern ML-based approaches to real business problems. - High fluency in analytics tooling-strong SQL skills and proficiency in Python and/or R for analysis, modeling, and automation. Preferred qualifications: - Experience with Databricks or similar cloud data platforms / warehouses. - Familiarity with Hex or other notebook-based analysis tools. - Experience in a high-growth startup and/or B2B business models (e.g., pipeline, CRM, RevOps data). #singapore #sydney #melbourne #london Applicant Safety Policy: Fraud and Third-Party Recruiters To protect you from recruitment scams, please be aware that Airwallex will not ask for bank details, sensitive ID numbers (i.e. passport), or any form of payment during the application or interview process. All official communication will come from an @airwallex.com email address. Please apply only through careers.airwallex.com or our official LinkedIn page. Airwallex does not accept unsolicited resumes from search firms/recruiters. Airwallex will not pay any fees to search firms/recruiters if a candidate is submitted by a search firm/recruiter unless an agreement has been entered into with respect to specific open position(s). Search firms/recruiters submitting resumes to Airwallex on an unsolicited basis shall be deemed to accept this condition, regardless of any other provision to the contrary. Equal opportunity Airwallex is proud to be an equal opportunity employer. We value diversity and anyone seeking employment at Airwallex is considered based on merit, qualifications, competence and talent. We don't regard color, religion, race, national origin, sexual orientation, ancestry, citizenship, sex, marital or family status, disability, gender, or any other legally protected status when making our hiring decisions. If you have a disability or special need that requires accommodation, please let us know.

Ibotta is seeking a Staff Data Scientist, Client Data & Measurement to join our innovative team and contribute to our mission to Make Every Purchase Rewarding. Our newly formed and growing Core Data Science Team provides high-quality, on-time data science-related products and services across all business areas and teams within Ibotta. We do this by providing thought leadership, subject matter expertise, evangelism and governance of business-critical data science initiatives. As a Staff Data Scientist, you’ll have the unique, challenging, and rewarding opportunity to build the foundation of data and data science within the company. You’ll be able to create and own greenfield opportunities to make big positive impacts on the business across several teams and business areas. You’ll have the chance to own the data science technology of one or more important core business domains, from collaborating with stakeholders, through the full model development lifecycle. You’ll be able to advance not only your technical skills, but your organizational and leadership skills as well, by establishing and leading best practices for the team and company, and providing mentoring and education across the company. This position is available in multiple locations: Denver, Colorado - if you are in or willing to relocate to the Denver area, this is a hybrid position requiring 3 days in office (Tuesday, Wednesday, and Thursday). Remote options are available for the following states - AZ, AR, CA, FL, GA, IL, IN, IA, KS, MD, MA, MI, MN, MO, MT, NV, NJ, NY, NC, OH, OK, PA, TN, TX, UT, VA, WA, WI. If you’re not in the Denver metro area or the listed states, relocation reimbursement to Denver is available. Not based in Denver? We will offer a relocation bonus to help make your move to the Mile High City a smooth one. What you will be doing: - Provide subject matter expertise and ownership of one or more of the company’s core business domains - Establish and lead best practices, setting the example for the team - Initiate and drive collaboration with stakeholders, architects, and data engineers to discover, define, cleanse, and refine the data needed for analysis and modeling - Analyze large and novel datasets to extract actionable insights to inform model development and understand consumer behavior - Provide customized views of large and complex datasets to support data analysis and business decision-making - Inform experimental design to formulate solutions addressing major business challenges and innovation opportunities - Build models using a variety of statistical and machine learning techniques, from selecting the best type of model for the problem to using advanced techniques to measure and optimize model performance - Harden data pipelines and models for production deployment and monitoring of performance over time - Provide mentoring and education to this team and other teams across the company - Embrace and uphold Ibotta’s Core Values of Integrity, Boldness, Ownership, Teamwork, Transparency, & A good idea can come from anywhere What we are looking for: - 7+ years of experience making significant positive impacts in a professional data science or machine learning role - Bachelor’s degree in Computer Science, Engineering, Analytics or a related field required - A history of and passion for driving important decisions using data and data storytelling - A love of learning and continuous development, including staying at the forefront of the latest advances in data science and machine learning. Broad-scale community contributions to the fields of data science and machine learning in the way of conference presentations, professional publications, and/or recognized internet presence are a strong plus - Expert-level knowledge, skills, and abilities in creating, developing, and applying a variety of new or existing machine learning and statistical algorithms - Expert-level Python and/or R knowledge, skills, and abilities. Spark or PySpark experience is a strong plus - Excellent statistical analysis skills, with a solid understanding of experimental design and time series analysis a strong plus - Superior analytical and problem solving skills - Expert-level knowledge, skills, and abilities in database manipulation, query languages, and graph data schemas - Experience manipulating complex data to apply business rules for improved feature engineering within data lakes, distributed systems, and data streams - Experience in MLOps a strong plus About Ibotta ("I bought a...") Ibotta (NYSE: IBTA) is a leading performance marketing platform allowing brands to deliver digital promotions to over 200 million consumers through a network of publishers called the Ibotta Performance Network (IPN). The IPN allows marketers to influence what people buy, and where and how often they shop – all while paying only when their campaigns directly result in a sale. American shoppers have earned over $2.6 billion through the IPN since 2012. The largest tech IPO in history to come out of Colorado, Ibotta is headquartered in Denver, and is continually listed as a top place to work by The Denver Post and Inc. Magazine. To learn more about what our Tech teams are doing day to day, visit Building Ibotta on Medium.com. - This position is located in Denver, CO and includes competitive pay, flexible time off, benefits package (including medical, dental, vision), Employee Stock Purchase Program, and 401k match. Denver office perks include paid parking, bagel Wednesdays, snacks and occasional meals. - Base compensation range: $152,000 - $203,000. This compensation range is specific to the United States labor market and may be adjusted based on actual experience. Total compensation for this role also includes a variable component in addition to base salary. - Ibotta is an Equal Opportunity Employer. Ibotta’s employment decisions are made without regard of race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected status. - Applicants must be currently authorized to work in the United States on a full-time basis. - Applicants are accepted until the position is filled. - For the security of our employees and the business, all employees are responsible for the secure handling of data in accordance with our security policies, identifying and reporting phishing attempts, as well as reporting security incidents to the proper channels. #LI-Remote #BI-Remote #BI-Hybrid

• Design, develop and deploy advanced statistical or machine learning models related to credit risk, pricing, collections, fraud, and other high-impact business use cases that drive better data-driven decisions • Execute the full model lifecycle, from initial data discovery and feature engineering to deployment, monitoring and iterative improvement • Partner with cross-functional teams including Portfolio Strategy, Collections, Engineering, Product, Underwriting, and Sales to integrate models into our applications and ensure they function seamlessly • Communicate complex technical concepts, model results, and business implications to both technical and non-technical stakeholders • Develop production-grade code and contribute to internal toolkits, documentation, and peer code review to ensure high-quality delivery • Build and maintain production machine learning pipelines and monitoring systems to ensure models are reliable, scalable and continuously improving

• Dive into various clinical and coding audits, unpacking the data that drives audit decisions, and understanding past outcomes. • Curate labeled data, hypothesize new features, and develop ML models that target claims for audit with even greater precision. • Measure model performance rigorously, translating outcomes into operational insights and recommendations for our clients. • Work with vast, nuanced data pipelines derived from intricate business workflows—often unclean and undefined—to refine them for robust modeling. • Enhance data pipelines, modeling infrastructure, and team tools to level up our capabilities and decision-making efficiency. • Build expertise in healthcare data and make an impact on the industry. Engage with clients and internal experts to refine model insights, ensuring alignment with real business needs.