Data Scientist (27)
Norfolk, Virginia, United States
- Contribute to the development and implementation of an enabling data science and AI capability at HQ SACT and for the NATO Enterprise.
- Identify, contribute to and implement ML/AI initiatives across HQ SACT and the NATO Enterprise with suggestions for ML approaches and implementation, including the processing of training data and performance assessment of machine learning techniques on datasets.
- Apply existing data science techniques to new problems and datasets using specialised programming techniques to meet needs of the project and customer.
- Evaluate the outcomes and performance of data science models. Identify and implement opportunities to train and improve models and the data they use.
- Publish reports on machine learning model outputs to meet customer needs and conforming to agreed standards.
- Has in-depth knowledge of NLP, ML engineering, or computer vision.
- Support review of data science and AI activities, processes, products or services.
- Work in conjunction with other data professionals, software engineers and SMEs from different functional areas.
- Support development and maintenance of data pipelines for structured and unstructured data.
- Provide subject matter expertise to (military and civilian) staff within HQ SACT or the NATO Enterprise and develop proofs of concept, as directed.
- Support internal and external communities that bring together DS & AI practitioners and consumers.
- Support development of scientific studies.
- Support educational efforts and training development related to data, AI or digital literacy.
- Remain up-to-date with new developments in data science and AI to bring innovative ideas into implementation.
- Support building a data-driven culture that uses analytics to generate insights, improve decision making at all levels, inform strategy and policy decisions, and improve performance.
- Perform additional tasks as required by the COTR related to the LABOR category.
Requirements
- A Master’s degree or higher at a nationally recognised/certified university in Data Science, Data Analytics, AI engineering, or a related discipline such as Mathematics, Physics, Computer Science, Software Engineering OR four years minimum professional experience in the area of Data Science, including providing analysis and advice in the field of data science, within the last five years.
- Proven work experience as a Data Scientist, ML Engineer or a similar role in the last four years.
- Proficient in Machine Learning/AI, statistical and mathematical analysis.
- Experience in modern software architecture and software development related to data science, analytics and data integration, e.g. Python, SQL, R, KNMIE.
- Experience with machine learning and AI frameworks, using e.g. TensorFlow, PyTorch, scikit-learn, or other modern machine learning frameworks.
- Experience with planning, executing and maintaining Data Science pipelines.
- Experience visualizing data and producing high quality graphs and reports, charts and interactive dashboards using tools such as Tableau, MS Power BI, and Kibana.
- Experience with agile methodologies.
- Experience in providing training in various areas related to data science, analytics, and AI at different technical levels.
- Portfolio of demonstrable products available via GitLab, or other platforms.
- Ability to work in a cloud environment, in particular Microsoft Azure, or Amazon Web Services.
- Working experience in an international environment with both military and civilian elements.
- Experience working within a Big Data ecosystem, with tools such as Databricks, Spark etc.
- Experience working with open source and publicly available data. 16.Experienced ‘data storyteller’.
- Experience working on a military staff.
- Knowledge of NATO organization and its functions.
- Experience in project management.
- NATO Secret clearance or national equivalent
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Architecture Azure Big Data Computer Science Computer Vision Data Analytics Databricks Data pipelines Engineering GitLab Kibana Machine Learning Mathematics NLP Open Source Physics Pipelines Power BI Python PyTorch R Scikit-learn Spark SQL Statistics Tableau TensorFlow Unstructured data
Perks/benefits: Career development
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