Data Scientist and Training Analyst

01 ago - Italia
Booz Allen Hamilton

The Opportunity:
Ever-expanding technology like IoT, machine learning, and artifi cia l intelligence means that there’s more structured and unstructured data available today than ever before. As a data engineer, you know that organizing data can yield pivotal insights when it’s gathered from disparate sources. We need an experienced data engineer like you to help our clients find answers in their data to impact important missions.
As a data engineer at Booz Allen, you’ll implement data engineering activities on some of the most mission-driven projects in the industry. You’ll deploy and develop pipelines and workflows that organize and make disparate data meaningful.
Here, you’ll work with and guide a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment. You’ll use your experience in analytical exploration and data examination while you manage the assessment, design, building, and maintenance of analytic solutions for your clients.
Work with us to use data for good.
You Have:




- 5+ years of experience in a data engineering or application development field
- 3+ years of experience designing, developing, operationalizing, and maintaining data applications for reporting and analytics at enterprise scale
- 3+ years of experience with Python, SQL, Scala, or R
- Experience creating solutions within a collaborative, cross-functional team environment
- Experience developing and delivering training materials, documentation, and workshops for data systems and tools.
- Secret clearance
- HS diploma or GED and 8+ years of experience in Data Science, or Associate's degree and 4+ years of experience in Data Science
- Active passport with at least 6 months validity for the purposes of visa applications

Nice If You Have:
- Experience with Palantir tools, such as Foundry or Gaia
- Experience with Advana or other DoD data analytics systems
- Experience with distributed data or computing tools, including Spark, Databrick

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