Associate Data Scientist - Algorithms and Data Insights
What makes Gartner a GREAT fit for you? When you join Gartner, you’ll be part of a fast-growing team that helps the world become smarter and more connected. We’re the world’s leading research and advisory company, achieving consistent double-digit growth by steering clients toward the right decisions with business and technology insights they can’t find anywhere else. Our associates enjoy a collaborative work environment, exceptional training and career development — as well as unlimited growth opportunities. If you like working with a curious, supportive, high-performing team, Gartner is the place for you.
The Algorithms and Data Insights team manages the end to end process of turning innovative ideas into data models and systems that drive significant business outcome. Our work involves generating ideas, creating business cases, and quickly developing models and to test in real world scenarios. The ideal candidate would be a champion of applying data science to improve client experiences. They would be willing to iterate quickly during model development, but be capable of building more complex algorithms when necessary.
Given the broad areas that we are responsible for, you will likely start in one domain but quickly get involved in other domains. A few potential projects include:
- Applying Natural Language Processing to improve our ability to synthesize client search queries so we offer best content based on their intent
- Using machine learning to develop self-correcting algorithms to improve our recommendation targeting in Email
- Using predictive modeling to develop forward-looking projections of client retention and purchasing.
- Using statistical analysis to evaluate and improve existing algorithms
- Conceptually mapping cause and effect relationships to statistical models to develop a robust understanding of business drivers
- 3-5 years hands-on experience building predictive models, recommendation systems, or NLP/text mining tools.
- Familiar with the foundation approaches to the major data science disciplines, such as data preparation, advanced statistics, machine learning, simulation, and natural language processing
- Practical, intuitive problem solver with a demonstrated ability to translate business objectives into actionable data science tasks and translate quantitative analysis into actionable business strategies
- Connections to the recommendations and / or information retrieval academic community
- Experience and proficiency with various programming languages (e.g., Python), machine learning tools (e.g., scikit-learn), statistical packages (e.g., Scipy), SQL/relational databases (e.g., Oracle) and NoSQL databass (e.g., MongoDB, graph database), Linux and shell scripting
- Masters in a quantitative research field (e.g., Computer Science, Electrical Engineering, Applied Mathematics, Physics, Neuroscience etc.). PhD preferred.
Job Requisition ID:29421
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