Associate Data Scientist - Spring 2027 Master's level graduates
About The Position
The Insights and Product Analytics (IPA) organization supports business performance across Gartner’s research products and analyzes the Business and Technology Insights business unit. Its work spans research content, client interaction, conferences and events, client retention, associate performance, budgets and financial analysis, and client demand sensing. The team provides data, insights, and analytical tools to support fact-based operational and strategic decisions. The Associate Data Scientist executes high-impact data modeling projects, from design and development through validation, communication, operationalization, implementation, and maintenance. The role delivers ad hoc modeling and analysis, converts business initiatives into actionable analytics projects, proposes new analytical innovations, and partners with business stakeholders, IT, and Project Management to design and deliver solutions. Applicable technologies include machine learning, artificial intelligence, generative AI, natural language processing, and statistical modeling. This opportunity is aimed at Spring 2027 master's-level graduates, with a bachelor's degree plus at least two years of related experience also accepted.
Requirements
- Master’s degree, or bachelor’s degree with at least two years of related experience.
- Previous data modeling experience in a business environment.
- In-depth knowledge of statistical principles and their application in modeling and data analysis.
- Experience developing and applying descriptive, predictive, and prescriptive models.
- In-depth natural language processing knowledge and application experience.
- Expertise in Python, SQL, and Spark.
- Basic skills in Power BI, Excel, and PowerPoint.
- Experience with multiple modeling techniques, such as time series, random forests, clustering, neural networks, generalized linear models, optimization, design of experiments, and dimensionality reduction.
- Experience with churn analysis, profiling, and recommendation systems.
- MLOps experience, including implementing models or algorithms in production systems.
- Ability to work in a fast-paced environment and deliver against milestones.
- Excellent communication skills in technical and business domains.
- Proven ability to influence key stakeholders and leaders.
- U.S. work authorization is required.
Nice To Haves
- Preferred degree in Engineering, Statistics, Computer Science, Mathematics, Applied Mathematics, Data Science, or a related field.
Responsibilities
- Execute large-scale, high-impact data modeling projects, including designing, developing, validating, socializing, operationalizing, and maintaining data-driven analytics.
- Provide ad hoc modeling and analytical insights for strategic and operational initiatives.
- Conduct analytics end to end, including understanding business issues, proposing technical solutions, data wrangling and cleaning, analysis, feature engineering, model selection and development, validation, operationalization, presenting results, implementation, and documentation.
- Translate top-down business initiative requirements into actionable data analytics projects and propose bottom-up analytics innovations.
- Communicate technical solutions and results to business stakeholders.
- Partner with business stakeholders, IT, and Project Management to design and deliver innovative analytics solutions.
- Apply relevant technologies, including machine learning, artificial intelligence, generative AI, natural language processing, and statistical modeling.
Benefits
- Generous paid time off.
- 401(k) match up to $7,200 per year.
- Opportunity to purchase company stock at a discount.
- Market-leading benefit programs.
- Annual bonus plan based on company and individual performance, or a role-based uncapped sales incentive plan, as applicable.
- Hybrid work environment with flexibility to work virtually when productive and gather with colleagues in person.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
