**Active TS/SCI w/Polygraph REQUIRED** Please do not apply if you do not currently possess this level of clearance.
Telework: None
Qualifications:
- Bachelor's degree from an accredited college or university in a quantitative discipline (e.g., statistics, mathematics, operations research, engineering or computer science) and five (5) years of experience analyzing datasets and developing analytics as well as five (5) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
- An additional four (4) years of experience in software development, cloud development, analyzing datasets, or developing descriptive, predictive, and prescriptive analytics can be substituted for a bachelor's degree.
- A PhD from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience.
- Produce data visualizations that provide insight into dataset structure and meaning
- Work with subject matters experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats (e.g., SQL tables, structured metadata, network logs)
- Incorporate SME input into feature vectors suitable for analytic development and testing
- Develop Al and machine learning models to address complex problems.
- Develop and optimize Large Language Models (LLM) for various NLP tasks and information retrieval
- Experience with utilizing GPU-based computing resources to accelerate model training and deployment.
- Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics
- Develop statistical tests to make data-driven recommendations and decisions
- Develop experiments to collect data or models to simulate data when required data are unavailable
- Develop feature vectors for input into machine learning algorithms
- Identify the most appropriate algorithm for a given dataset and tune input and model parameters
- Evaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices)
- Oversee the development of individual analytic efforts and guide team in analytic development process
Job Description:
- A data scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.
Salary: $200,000 - $250,000 annually
Excellent benefits package including 25 days PTO, 11 paid holidays, 100% employer-paid healthcare for employees and dependents - available day 1, 8% 401(k) employer match - immediate vesting.
Disclaimer: The salary range provided is an estimate based on current market conditions and may be adjusted based on factors such as experience, skills, and qualifications. The final salary offer will be determined after a thorough review of the candidate's background and alignment with the role. Please note that this range is subject to change and should be considered as a guideline rather than a definitive figure.
Shield Consulting Solutions is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.
This is a full time position
