Amivero is looking for a Data Scientist to develop complex data models in support of a federal client's workforce planning strategy, using machine learning and deep learning models and algorithms to create useful and actionable insight for customers.
Requirements
- Experience with Natural Language Processing, Machine Learning Models, Question Answering, Text Mining, Information Retrieval, Distributional Semantics, Knowledge Engineering
- Experience using a variety of mathematical, statistical, data mining, and data analysis methods/tools
- Working knowledge of general machine learning algorithms and NLP, Graph Theory, and Network Analysis
- Fluency in one or more programming languages (e.g., Python, JavaScript, R, etc.)
- Experience with statistical data analysis, experimental design, and hypotheses validation
- Experience with database querying like SQL
- Experience with productization of machine learning algorithms and the ability to deliver data science components that are part of successful deliverables
Responsibilities
- Perform knowledge elicitation from customer subject matter experts and convert that to derived algorithms
- Analyze large data sets to identify actionable insights with mathematical statistical rigor
- Rigorously critique and correct intermediate results to improve the algorithmic outcomes
- Design and deploy deep learning algorithms and predictive models
- Develop custom data models and algorithms to apply to data sets
- Assess the effectiveness and accuracy of new data sources and data gathering techniques
- Develop dashboards to present to leadership and draw insights from data models
Other
- US Citizenship Required to obtain Public Trust
- Active DHS or CBP Public Trust clearance preferred
- 3+ years of relevant experience
- BA/BS in Computer Science, Statistics, Applied Mathematics, Computational Linguistics, Artificial Intelligence or related field
- Interpersonal skills and the ability to communicate effectively with various clients in order to explain and elaborate on technical details
