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We are looking for an econometrician to join Mastercard’s Economics Institute’s data science and econometrics team. This individual will be critical to growing the institute’s ability to support and enhance revenue products like advisory services, disseminate content to our stakeholders, and quantitative research outputs. This client interfacing role provides the opportunity to work with leading companies across different industries and deliver insights using unique, rich, multi-faceted data sources & developing frontier level insights and methods.
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
Leverage Mastercard data to improve contemporaneous macro forecasting via nowcasting
Improve variable selection and reduction techniques to identify high quality predictive variables
Improve model estimation approaches and model back testing
Identify patterns or anomalies in the datasets being explored, produce concise insights for the Economist to allow fast interpretation of results
Research and integrate econometric and statistical models as needed in order to create insights and compelling visualizations of data trends to develop interactive dashboards/apps for client presentations
Work closely with our customers, client services, economic advisory product and customer teams to translate client pain points/requirements into business and data specifications, clear data structure and eventually a usable data set/model/forecast/insights
Participate in every stage of a project from briefing to ideation, to content development to draft/prototyping, testing, feedback collection and finalization
Requirements:
Creative & passionate about statistics/math, economics, data, technology, and its applications, with an entrepreneurial mindset open to new ideas
A good foundation in different modeling approaches and demonstrated success in managing large models
A demonstrated interest in different machine learning and statistics with the ability to communicate models in a non-technical manner
Expertise in one or more of R, Python, Julia, MATLAB or similar languages
Interest/experience in some of the following: machine learning (supervised and unsupervised), NLP, time series analysis, and text analysis on economic and financial data sets
Quantitative modeling experience 2-4+ years, ideally in a tech, healthcare/financial or academic research field
Good foundation in economics with an advanced degree in math/statistics/quantitative field
Strong collaborator and independent thinker
Previous client facing experience, proficient in synthesizing data to create insights, great storyteller
Excellent at managing multiple projects and tight timelines with an ability to reprioritize as situation might require and staying calm under pressure
Evidence of creativity/innovation/unorthodox thinking in data driven economics