Role Description This is a senior, hands-on technical leadership role for someone who can design, build, and scale end-to-end GenAI systems — from architecture decisions to production deployment. - Lead LLM-based solution design (RAG, agents, fine-tuning strategies) - Build end-to-end GenAI applications (data retrieval orchestration APIs UI) - Own critical architectural decisions (model selection, vector DBs, pipelines) - Implement AI governance, safety, and compliance layers (PII, guardrails, monitoring) - Mentor engineers and drive AI best practices across teams Qualifications - 6+ years in Data Science / AI Engineering - 4+ years building production-ready Python systems - 2+ years delivering real-world LLM / GenAI applications - Proven experience with RAG pipelines (design + optimization) - Strong understanding of LLM trade-offs (RAG vs fine-tuning vs hybrid) - Experience making architecture-level decisions - Fluent English & strong stakeholder communication Requirements - Experience with LlamaIndex / LangGraph - Exposure to multimodal models - Experience with Azure cloud ecosystem - Ability to build lightweight UIs / demos for AI systems - Mentoring junior & mid-level engineers Benefits - Direct ownership of enterprise-scale GenAI systems - Opportunity to shape AI architecture decisions end-to-end - Exposure to global clients across multiple industries - Strong learning ecosystem (110+ trainings/year + Udemy access) - Clear path toward technical leadership and influence

Role Description This is a senior, hands-on technical leadership role for someone who can design, build, and scale end-to-end GenAI systems — from architecture decisions to production deployment. - Lead LLM-based solution design (RAG, agents, fine-tuning strategies) - Build end-to-end GenAI applications (data retrieval orchestration APIs UI) - Own critical architectural decisions (model selection, vector DBs, pipelines) - Implement AI governance, safety, and compliance layers (PII, guardrails, monitoring) - Mentor engineers and drive AI best practices across teams Qualifications - 6+ years in Data Science / AI Engineering - 4+ years building production-ready Python systems - 2+ years delivering real-world LLM / GenAI applications - Proven experience with RAG pipelines (design + optimization) - Strong understanding of LLM trade-offs (RAG vs fine-tuning vs hybrid) - Experience making architecture-level decisions - Fluent English & strong stakeholder communication Requirements - Experience with LlamaIndex / LangGraph - Exposure to multimodal models - Experience with Azure cloud ecosystem - Ability to build lightweight UIs / demos for AI systems - Mentoring junior & mid-level engineers Benefits - Direct ownership of enterprise-scale GenAI systems - Opportunity to shape AI architecture decisions end-to-end - Exposure to global clients across multiple industries - Strong learning ecosystem (110+ trainings/year + Udemy access) - Clear path toward technical leadership and influence

Role Description As part of the Data Engineering team, Fox Cable Network Services, LLC seeks a Data Scientist (MLOps Engineer) to focus on deploying, managing, and scaling machine learning models within Fox’s AWS and Databricks environments. Play a crucial role in ensuring Fox’s ML (machine learning) models are deployed reliably, maintained efficiently, and deliver value across the organization. Work effectively with multiple internal stakeholders across diverse groups such as Fox Sports, Fox News Media, Fox Entertainment, and Fox Television Stations to support a wide array of Data Science and Data Engineering initiatives. - Design, implement, and maintain robust, scalable ML pipelines for the production and deployment of machine learning models. - Collaborate closely with other data scientists, data engineers, and DevOps to ensure seamless integration and performance of models in AWS and Databricks environments. - Build automated workflows for model deployment, monitoring, and retraining, ensuring high availability and reliability. - Develop processes for tracking, logging, and versioning of models to support reproducibility and auditability. - Implement monitoring solutions to track model performance and data drift, providing insights to maintain and improve model quality over time. - Troubleshoot, debug, and optimize ML pipelines to improve efficiency and reduce latency. - Stay updated with the latest advancements in MLOps tools and practices, ensuring that Fox infrastructure remains cutting-edge and future-ready. Telecommuting permitted from any location in the U.S. Qualifications - Master’s degree in Data Science, Computer Science, Information Technology, Engineering or related field. - Two (2) years of experience in data science or related experience in MLOps/DevOps. - Experience deploying and maintaining ML models in production. - Building CI/CD pipelines for ML models using tools such as Git and Jenkins. Requirements - Experience in ML frameworks such as TensorFlow, PyTorch and scikit-learn. - Experience in SQL, Python, Docker, and Kubernetes. - Knowledge of monitoring and logging tools used to track model performance and data quality such as Prometheus, Grafana and CloudWatch. - Experience with A/B testing and experiment design. - Experience with product analytics and working with event-level data. - Experience in Databricks and AWS services such as S3, EC2, SageMaker and Lambda. - Any level of experience or knowledge in the specific skills is acceptable. Benefits - Medical/dental/vision insurance. - 401(k) plan. - Paid time off. - Other benefits in accordance with applicable plan documents. - Benefits for Union represented employees will be in accordance with the applicable collective bargaining agreement. Company Description Fox Corporation produces and distributes content through some of the world’s leading and most valued brands, including: FOX News Media, FOX Sports, FOX Entertainment, FOX Television Stations and Tubi Media Group. We empower a diverse range of creators to imagine and develop culturally significant content, while building an organization that thrives on creative ideas, operational expertise and strategic thinking.

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.