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Deloitte Data Science Developer (Python/JavaScript) with TS/SCI Polygraph - Chantilly, VA in McLean, Virginia

In this age of disruption, organizations need to navigate the future with confidence by tapping into the power of data analytics, robotics, and cognitive technologies such as Artificial Intelligence (AI). Our Strategy & Analytics portfolio helps clients leverage rigorous analytical capabilities and a pragmatic mindset to solve the most complex of problems. By joining our team, you will play a key role in helping to our clients uncover hidden relationships from vast troves of data and transforming the Government and Public Services marketplace.

Work you'll do:

Candidate will join a team of high-performing data scientists and data engineers to deliver cutting-edge analytics for high-visibility national security missions.

  • Develop and maintain software applications using Python or JavaScript.

  • Design and implement automation solutions to streamline processes and improve efficiency.

  • Build interactive and informative dashboards using tools such as Matplotlib, Power BI, or Tableau.

  • Handle the complete ETL (Extract, Transform, Load) process for data integration and management.

  • Collaborate with cross-functional teams to gather requirements and deliver high-quality software solutions.

  • Troubleshoot and debug code to ensure optimal performance and functionality.

  • Stay up to date with the latest industry trends and technologies to continuously improve our software development practices.

The Team:

Deloitte's Government and Public Services (GPS) practice - our people, ideas, technology and outcomes-is designed for impact. Serving federal, state, & local government clients as well as public higher education institutions, our team of over 15,000+ professionals brings fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise.

The GPS Analytics and Cognitive (A&C) offering is responsible for developing advanced analytics products and applying data visualization and statistical programming tools to enterprise data in order to advance and enable the key mission outcomes for our clients. Our team supports all phases of analytic work product development, from the identification of key business questions through data collection and ETL, and from performing analyses and using a wide range of statistical, machine learning, and applied mathematical techniques to delivery insights to decision-makers. Our practitioners give special attention to the interplay between data and the business processes that produce it and the decision-makers that consume insights.

Qualifications:

Required:

  • Bachelor's degree from an accredited college or university

  • 2+ years of experience with Python and/or JavaScript

  • Experience with version control systems

  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future

  • Must be able to work fully onsite in Chantilly, VA

  • Candidates must be at least 18 years of age at the time of employment

Preferred:

  • Master's Degree

  • Experience in building dashboards using Matplotlib, Power BI, or Tableau

  • Strong understanding of automation techniques

  • Familiarity with the ETL process and data management best practices

  • Strong problem-solving skills and the ability to work independently

  • Excellent communication and collaboration skills

  • Ability to manage multiple projects simultaneously and meet deadlines

  • Knowledge of databases (e.g., SQL, NoSQL) and API integration is a plus

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Information for applicants with a need for accommodation: https://www2.deloitte.com/us/en/pages/careers/articles/join-deloitte-assistance-for-disabled-applicants.html

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All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.

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