Associate Analyst

Presidio•,

About The Position

Presidio is seeking an Associate Analyst to join our cloud Data Science team. This role involves performing comprehensive analysis of customer cloud infrastructure costs and utilization to identify optimization opportunities, providing insights to support informed decision-making regarding Cloud customer offerings, assessing and evaluating risks associated with cloud operations and developing mitigation strategies, identifying trends and patterns in cloud usage to anticipate future requirements and resource allocation, and collaborating on the creation of predictive and classification models to enhance efficiency and decision-making.

Requirements

  • Bachelor's degree or the equivalent work experience and/or military experience
  • 1-3 year's experience with Cloud Data (e.g. AWS, GCP, Azure)
  • 1-3 year's experience with data analysis
  • Experience with one or more tools such as Tableau, matplotlib, seaborn, ggplot2, AWS Quicksight or any other relevant BI toolset.
  • Proficiency in cloud platforms (e.g., AWS, Azure, GCP) as well as Excel
  • Detailed oriented with the ability to complete tasks independently and in a timely manner
  • Experience in data analysis, data wrangling, modeling, and risk assessment
  • Must be a US Citizen

Nice To Haves

  • Master's degree in a relevant field (e.g., Data Science, Cloud Computing, Business Analytics preferred)
  • Knowledge of cloud cost optimization strategies is a plus
  • Strong analytical and problem-solving skills.
  • Excellent communication and teamwork skills.

Responsibilities

  • Perform comprehensive analysis of our current customer cloud infrastructure costs and utilization to identify opportunities for optimization.
  • Provide insights and analysis to support informed decision-making in relation to our Cloud customer offerings.
  • Assess and evaluate risks associated with cloud operations, and develop strategies to mitigate them.
  • Identify trends and patterns in cloud usage to anticipate future requirements and resource allocation.
  • Collaborate on the creation of predictive and classification models to enhance efficiency and decision-making.
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