Data Scientist

Avalore, LLC•Arlington, VA

12h•$89,000 - $202,000•Onsite

About The Position

The Data Scientist will develop AI/ML models through training, fine-tuning, feature engineering, benchmarking, and deployment preparation. This person will apply scientific methodology to extract insights and create predictive capabilities from data. This person will analyze complex datasets to identify patterns and relationships, select and implement appropriate machine learning algorithms for specific problems, and develop feature engineering approaches to improve model performance. This person will design and execute model validation and testing procedures, tune hyperparameters to optimize model performance, and prepare models for production deployment. This person will create data visualizations to communicate findings and model results, collaborate with subject matter experts to incorporate domain knowledge, and document methodologies and results. This person will stay current with advances in data science techniques, evaluate new algorithms and approaches for potential adoption, and mentor junior data scientists. This person will ensure models meet requirements for accuracy, performance, and explainability, collaborate with AI/ML engineers for model deployment, and participate in data governance activities. This person will develop and implement data science workflows and methodologies, contribute to research initiatives, and support business stakeholders in interpreting model outputs.

Requirements

SECRET Security Clearance Required
CCSP,CFR,FITSP-M,GSEC,Security+, or SSCP certification (for Junior/Journeyman roles)
SecurityX/CASP+,GCSA,GSLC, or CISSP (for Senior roles)
Bachelor's Degree
Good communication skills
Self-starter mindset
Professional proficiency in English is required.
Demonstrated proficiency in using all Microsoft Office applications.
Currently authorized to work in the United States on a full-time basis.
Avalore will not sponsor applicants for work visas for this position.

Responsibilities

Develop AI/ML models through training, fine-tuning, feature engineering, benchmarking, and deployment preparation.
Apply scientific methodology to extract insights and create predictive capabilities from data.
Analyze complex datasets to identify patterns and relationships.
Select and implement appropriate machine learning algorithms for specific problems.
Develop feature engineering approaches to improve model performance.
Design and execute model validation and testing procedures.
Tune hyperparameters to optimize model performance.
Prepare models for production deployment.
Create data visualizations to communicate findings and model results.
Collaborate with subject matter experts to incorporate domain knowledge.
Document methodologies and results.
Stay current with advances in data science techniques.
Evaluate new algorithms and approaches for potential adoption.
Mentor junior data scientists.
Ensure models meet requirements for accuracy, performance, and explainability.
Collaborate with AI/ML engineers for model deployment.
Participate in data governance activities.
Develop and implement data science workflows and methodologies.
Contribute to research initiatives.
Support business stakeholders in interpreting model outputs.