Deloitte

location-iconDeloitte

Data Scientist Manager

location-iconDouglas, MA, 01516

jobtype-iconPart Time, Full Time

estimated-salary-icon$119,871 per year

dateposted-iconPosted 9 days ago

Apply Now

location-iconActively Hiring

About the Role

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 solve our clients' most complex business challenges. Join us to design our clients' roadmap to the future and transform the public sector marketplace.

Work You'll Do

As a Data Scientist Manager, you will work directly with federal clients to define strategies, drive technical development, and create next-generation AI tools and services. Your work will include state-of-the-art methodologies in areas like computer vision, natural language processing, time series analysis, preventative maintenance, signal processing, and workflow automation.

Key responsibilities include:

  • AI & Machine Learning Development: Design and apply advanced AI methods, leveraging GANs, CNNs, RNNs, LSTMs, BERT, and other models to address complex challenges.
  • Thought Leadership: Develop whitepapers, executive briefings, presentations, and other materials to support AI solutions.
  • Client Strategy: Guide federal clients on AI strategy, conduct exploratory data analysis, build/validate models, and deploy them in on-premise or cloud environments.
  • Subject Matter Expertise: Serve as an expert for GPS clients and the global AI partner ecosystem.
  • Scalable Solutions: Create repeatable processes and scalable data systems that address technical and deployment challenges.
  • Best Practices: Maintain and enforce data science best practices, staying updated on methodologies, industry trends, and open-source technologies.
  • Collaboration: Work cross-functionally with scientists, engineers, account managers, and leadership to ensure project success.

About the Team

SFL Scientific, a Deloitte business, is a U.S.-based data science consulting firm specializing in machine learning and AI technologies. The team develops complex AI systems using large and intricate data streams from advanced aerospace, defense, intelligence, and energy systems within the Government & Public Services (GPS) sector.

Qualifications

Required:

  • Master’s or Ph.D. in a STEM field preferred, with strong proficiency in Artificial Intelligence and related engineering technologies.
  • 8+ years of experience in AI/ML algorithm development and data analysis (e.g., NLP, time-series analysis, computer vision).
  • 5+ years of experience in programming and data science tools (Python, Keras, TensorFlow, PyTorch, Pandas, Scikit-learn, Jupyter, etc.).
  • 5+ years of experience in deployment and optimization (e.g., Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow).
  • Ability to obtain and maintain a government security clearance.
  • Must be legally authorized to work in the U.S. without employer sponsorship.
  • Willingness to travel up to 5%.
  • Experience coaching or mentoring junior staff.

Preferred:

  • 3+ years of experience with cloud deployment (AWS, Azure, GCP), including building and scaling solutions in AWS SageMaker.
  • Strong problem-solving and troubleshooting skills with the ability to exercise mature judgment.
  • Active security clearance.

Additional Information

For applicants requiring accommodations, please visit:Deloitte Assistance for Disabled Applicants.

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FAQ's

Find the answers for the most frequently asked questions below

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A data scientist is a professional who uses statistical analysis, machine learning, and programming skills to extract insights and knowledge from large, complex datasets. They often work on projects that involve predictive modeling, data mining, and visualization to help organizations make informed decisions.

Yes, a data scientist can work from home. They primarily work with data, which can be accessed remotely, and their tasks often involve analysis, modeling, and interpretation, which can be done independently. However, the specific work arrangements may vary depending on the company's policies and project requirements.

A Bachelor's degree in Mathematics, Statistics, Computer Science, or a related field is often considered suitable for a Data Scientist role. However, many data scientists also have advanced degrees such as a Master's or Ph.D. in Data Science, Statistics, or a related field. Practical experience with programming languages like Python, R, or SQL, and a strong understanding of machine learning and statistical analysis are also crucial.

Data scientists, like many professionals, can earn a significant income, but their salary can vary greatly depending on factors such as location, industry, and level of experience. However, it's important to note that wealth is not solely determined by income and can also depend on factors such as spending habits, investments, and career longevity.

A good data scientist should possess strong analytical skills, proficiency in programming languages like Python or R, and a deep understanding of statistical methods and machine learning algorithms. They should also be able to communicate complex data insights effectively to non-technical stakeholders.

To become a Data Scientist, follow these steps: 1. Obtain a strong foundation in mathematics and statistics. 2. Learn programming skills, particularly in languages like Python or R. 3. Gain experience with data analysis tools such as SQL, Tableau, or PowerBI. 4. Familiarize yourself with machine learning algorithms and libraries like scikit-learn or TensorFlow. 5. Build a portfolio of projects showcasing your data analysis and modeling skills. 6. Stay updated with the latest trends and advancements in the field.

A data scientist is a professional who uses statistical methods, machine learning algorithms, and data analysis techniques to extract insights, trends, and patterns from complex data sets, often to inform business decisions and strategy.

The number of data scientists is not inherently too many or too few, as the demand for data scientists is driven by the need for data analysis and interpretation in various industries. However, the supply may exceed the demand in certain regions or industries, leading to competition for positions. The optimal number of data scientists is subject to market dynamics and the availability of data-driven opportunities.

Yes, data scientists are scientists. They apply scientific methods, mathematics, and statistics to extract insights and knowledge from data. They work in various fields, such as technology, finance, healthcare, and more, to analyze and interpret complex data sets.