The Insights and Product Analytics team (IPA) organization is responsible for business performance of all research products and performs analysis related to all aspects of Gartner’s Business and Technology Insights business unit . This includes client value drivers: Research content, Client interaction, and the insights into conferences and events. IPA also supports the BTI organization by enabling and performing analysis running from client retention analytics, associate performance analytics, budget and financial analysis (in partnership with the finance organization), and client demand sensing. We power fact-based decision making by providing data, insights, and analytic tools to continuously improve our business – operationally and strategically . We’re committed to attracting the most creative, talented, and motivated students for our Associate Data Scientist and Data Scientist roles . What you’ll do: ● Execute large scale, high impact data modeling projects with responsibility for designing, developing, validating , socializing, operationalizing, and maintaining data-driven analytics that provide business insights to increase operational efficiency and customer value. ● Provide ad hoc modeling and analytical insights to inform strategic and operational initiatives. ● Conduct all phases of the analytics process. Including: Understanding business issues, proposing technical solutions, data wrangling, data cleaning, data analysis, feature engineering, model selection, model development, model validation, model operationalization, presentation of results and insights, model implementation, model documentation. ● Convert “ top-down ” business initiative requirements into actionable data analytics projects as well as conceiving and proposing “ bottom-up ” analytics innovations. ● Communicate technical solutions and results to business stakeholders. ● Partner with business stakeholders, IT, Project Management and lead the design and delivery of innovative analytics solutions. ● Inject the most applicable technology, including Machine Learning, Artificial Intelligence, Generative AI, Natural Language Processing, and Statistical Modelling.
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Job Type
Full-time
Career Level
Entry Level
Number of Employees
5,001-10,000 employees