About

• Apply data analysis, AI, and modelling techniques to understand user behaviour, identify opportunities, and inform product improvements. Write robust, reusable, and extensible code to support analysis, modelling, and operationalization at scale. Use AI-powered tools in your daily work to accelerate analysis, experimentation, and solution development. Develop and maintain metrics and evaluation frameworks to assess the quality, performance, and impact of services. Drive data-driven decision making by presenting clear, actionable insights to senior leaders and stakeholders. Collaborate in a cross-functional environment with local and remote partners to deliver scalable, elegant, and impactful solutions. Acquire, prepare, and validate datasets for analysis and modelling, while contributing to best practices in data collection and data quality. Evaluate and improve existing products to ensure intelligent services evolve to meet user needs. Design, evaluate, and optimize prompts and fine-tuning strategies for large language models. Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. 2+ years customer-facing, project-delivery experience, professional services, and/or consulting experience. These requirements include but are not limited to the following specialized security screenings: Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. Software engineering experience covering software engineering best practices (code quality, repo hygiene, code reviews, unit testing, design documentation, continuous integration, deployment). Track record of defining, delivering, and optimizing explorative data science and machine learning projects that address real-world problems. Knowledge of distributed big-data computing systems (e.g. Spark, Hadoop, Hive, Azure ML). Experience in experimentation frameworks and understanding how to measure end user impacting metrics. Experience with ML tools to build models and analyze data (e.g. Python, R, scikit-learn, TF, PyTorch, ML.NET). Experience with large language models (LLMs), including prompt engineering, fine-tuning, and evaluation for real-world applications