Data Scientist, AI and Analytics Consultant

1 week ago

Seattle, Washington, United States Gartner Full time
About the Role

Gartner's Consulting business is an extension of Gartner's industry-leading IT Research. From CIOs, to leaders in business and government, we help Gartner clients across enterprises translate insights into transformational actions and achieve their mission-critical priorities.

We deliver value to clients in areas such as IT Strategy Consulting, Benchmarking, Analytics and Optimization. Typically, this helps Gartner's clients to execute on their strategic priorities, across all sectors, including:

  • Digital Growth and Transformation
  • Applications, Infrastructure and Security Modernization
  • Sourcing and Spent Optimization
The Role

You will help our clients navigate the complex world of modern AI, data science and analytics. We'll look to you to provide our clients with a unique business perspective on how data science and analytics can transform and improve their entire organization - starting with key business issues they face.

This is a high growth, high visibility area with plenty of opportunities to enhance your skillset and build your career.

Key Responsibilities
  • Ability to lead and manage consulting engagements and diverse teams of experts and delivery associates.
  • Work with clients to identify the business potential of Artificial Intelligence (AI) and establish AI strategies, define and prioritize AI use cases, establish AI governance, and collaborate with client stakeholders to understand technical and business constraints.
  • Collaborate with clients to establish AI programs and processes for scaling delivery of AI solutions (e.g., MLOPs, ModelOps)
  • Align AI strategies and use cases to required data assets, identify strategies for acquiring data assets (including the potential value of synthetic data), design data pipelines to support data science and AI projects.
  • Apply various Machine Learning (ML) and analytics techniques to develop classification and prediction models and leverage foundation models to develop generative AI capabilities; integrate client, domain (e.g., finance, sales) and industry knowledge into the solution.
  • Collaborate with cross-functional teams to identify business problems and design experiments to test hypotheses.
  • Present findings, insights, and recommendations to both technical and non-technical stakeholders in a clear and concise manner.
  • Stay up-to-date with the latest advancements in data science, machine learning, and related fields, and apply them to improve existing processes and methodologies.
Requirements
  • Bachelor's or Master's degree in a quantitative field such as Computer Science, Data Engineering or related discipline.
  • Three to six or more years of relevant project experience in successfully launching, planning, executing data science projects. Preferably in the context of a consulting engagement.
  • Basic coding knowledge and experience in several languages for example: R, Python/ Jupyter, SAS, Java, Scala, C++, Excel, MATLAB, etc.
  • Experience with popular database programming languages including SQL, PL/SQL, others.
  • Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
  • Basic knowledge and experience in statistical and data mining techniques such as: generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN), T-distributed Stochastic Neighbor Embedding (t-SNE), graph analysis, etc.
  • Experience with data visualization tools and techniques to effectively communicate insights and findings.
  • Excellent problem-solving skills and ability to think critically to tackle complex business problems.
  • Strong communication and presentation skills, with the ability to convey technical concepts to non-technical stakeholders.
  • Ability to work independently and collaboratively in a fast-paced and dynamic environment.
  • Proven track record of delivering high-quality results within deadlines.

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