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Deloitte Data Scientist Manager in Rosslyn, Virginia

Do you want to build your brand by working for a leading consulting firm that drives eminence in the marketplace? Are you interested in leveraging your analytical skills and strategic ideas to improve mission execution? If so, Deloitte could be the place for you! Our Government and Public Services (GPS) Strategy and Analytics team brings deep industry expertise, rigorous analytical capabilities and a pragmatic mindset to help solve our client's most complex business problems. Join our team and play a key role in helping to design our clients' roadmap to the future and help transform the public sector marketplace.

Work You'll Do

In this role, the Data Scientist Manager will work directly with our federal clients to define

strategy, drive technical development, and create the next generation of AI tools and

services that include state-of-the-art methodologies in computer vision, natural

language processing, time series analysis, preventative maintenance, signal processing,

and automation of analyst workflows.

The Data Scientist Manager will:

• Design, develop and apply state-of-the-art methods within AI and machine learning, including the utilization of GANs, CNNs, RNNs, LSTMs, BERT, and other models to solve complex problems

• Act as an AI thought leader, including the creation of whitepapers, presentations, executive briefings, reports, and other materials to support AI solutions and services

• Guide federal clients with high autonomy in AI strategy and development, including understanding agency needs, performing exploratory data analysis, building and validating models, and deploying models into both on-prem and cloud environments

• Act as a subject matter expert to GPS clients and global AI partner ecosystem

• Iterate on and/or create repeatable, reusable processes and scalable data systems that meet technical and deployment challenges

• Maintain and uphold data science best practices on new methodologies, technologies, industry trends, and open source packages

• Work cross-functionally with other scientists & data engineers, federal account manager and leadership to help ensure project delivery and success

The team

SFL Scientific, a Deloitte Business, is a U.S. based, data science consulting firm

specializing in machine learning and AI technologies. We are looking for a senior data

scientist to design and build end-to-end AI solutions within Government & Public

Services (GPS). The candidate will be responsible for the development of AI systems

through leveraging large and complex data streams derived from the world's most

advanced aerospace, defense, intelligence, and energy systems.

Qualifications

Required:

• Master's or Ph.D. preferred in a STEM field, high proficiency in Artificial Intelligence and related engineering technologies

• 8+ years of experience in AI/ML algorithm development and data analysis (NLP, time-series analysis, computer vision)

• 5+ years of experience in in core programming languages and data science packages (Python, Keras, Tensorflow, PyTorch, Pandas, Scikit-learn, Jupyter, etc.)

• 5+ years of experience with deployment and optimization-Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow etc.

• Ability to obtain and maintain a government security clearance

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

• Willingness to travel up to 5%

• Experience coaching or mentoring junior staff

Preferred:

• 3+ years of Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker

• Strong problem solving and troubleshooting skills with experience exercising mature judgment

• Active Security clearance

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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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