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We are looking for an analyst to join Mastercard’s Economics Institute’s Applied Research team. This individual will be critical to growing the Institute’s ability to deliver economic insights, enhance revenue-generating products, and support advisory services. The analyst will work with unique, multi-faceted data sources to develop cutting-edge models and actionable insights that inform strategic decisions.
Job Responsibility:
Develop and improve models across the entire pipeline – from data ingestion to statistical modeling, including macro scenarios, and communicating the results to key stakeholders
Build, backtest, validate, and monitor forecasting models
Improve variable selection and reduction techniques to identify high quality predictive variables
Detect patterns or anomalies in datasets and produce concise insights for economists
Research and integrate econometric and machine learning models in order to create insights and compelling visualizations of data trends to develop interactive dashboards/apps for client presentations
Collaborate with customers, client services, and economic advisory teams to understand and translate client pain points and requirements into detailed business and data specifications. Design and define clear data structures to support the development of robust datasets, models, forecasts, and actionable insights. Ensure deliverables meet client needs by aligning technical solutions with business objectives
Participate in every stage of a project from briefing to ideation, to content development to draft/prototyping, testing, feedback collection and finalization
Requirements:
Creative and passionate about economics, machine learning, data, technology, and its applications, with an entrepreneurial mindset
Demonstrated experience in different machine learning and statistics models with the ability to communicate models in a non-technical manner
Proficient in one or more of R, Python, or similar languages
experience with SQL and Tableau is a plus
Demonstrated success in modeling with big data and experience with tools such as Spark, Hadoop, Hive is strongly preferred
Experience applying AI techniques, including large language models (LLMs), to economic modeling and forecasting is a strong plus
Quantitative modeling experience 1-2 years, ideally in a tech, financial or academic research field
Good foundation in economics with an advanced degree in math/statistics/quantitative field
Excellent at managing multiple projects and staying calm under pressure
Nice to have:
Experience with SQL and Tableau is a plus
Demonstrated success in modeling with big data and experience with tools such as Spark, Hadoop, Hive is strongly preferred
Experience applying AI techniques, including large language models (LLMs), to economic modeling and forecasting is a strong plus