Data Scientist
Staffed4U
Data Scientist Location: Linthicum Heights, MD
Work Schedule: Full-Time
Clearance Required: Active TS/SCI with Polygraph
Note: Position location is subject to change based on central Maryland client needs. Position Overview We are recruiting for a Data Scientist to support a client in Linthicum Heights, MD. This role will help develop capabilities that move system security evaluation and authorization away from manual processes and toward a more automated, streamlined, and continuously monitored model. The ideal candidate will have strong experience analyzing complex datasets, developing analytics, building predictive models, and using Python and other data analysis tools to support security, compliance, and Risk Management Framework automation. Key Responsibilities
Ideal Candidate Profile The ideal candidate is an experienced cleared Data Scientist who enjoys working with complex datasets, building analytics, and using automation to improve security and compliance processes. This person should be comfortable working with Python, predictive models, ETL pipelines, dashboards, and security-related data to support continuous monitoring and RMF automation. Equal Opportunity Employer We are committed to fostering an inclusive workplace and welcome qualified applicants from all backgrounds. Employment decisions are based on qualifications, experience, clearance eligibility, and client requirements.
Work Schedule: Full-Time
Clearance Required: Active TS/SCI with Polygraph
Note: Position location is subject to change based on central Maryland client needs. Position Overview We are recruiting for a Data Scientist to support a client in Linthicum Heights, MD. This role will help develop capabilities that move system security evaluation and authorization away from manual processes and toward a more automated, streamlined, and continuously monitored model. The ideal candidate will have strong experience analyzing complex datasets, developing analytics, building predictive models, and using Python and other data analysis tools to support security, compliance, and Risk Management Framework automation. Key Responsibilities
- Use Python as a primary language to process and analyze data to help determine whether resources and systems are secure.
- Identify outliers and trends to help track systems as they move through the Risk Management Framework lifecycle .
- Analyze resource attributes to determine which system a resource belongs to by comparing lost or unidentified resources against known system information.
- Design, develop, and maintain ETL pipelines to extract security and compliance data from multiple sources, including network sensors, security tools, and compliance databases.
- Transform data for analysis, reporting, and automated assessments.
- Load data into target repositories to support continuous monitoring and RMF automation.
- Support data engineering operations, including data quality validation, pipeline monitoring, and workflow optimization.
- Ensure reliable, scalable, and timely delivery of security-related data to support decision-making.
- Create analytics, dashboards, charts, and reports to help stakeholders understand security and compliance data.
- Build, tune, and test predictive models to support security and compliance outcomes.
- Active TS/SCI with Polygraph .
- 3-10+ years' experience
- Bachelor's and master's degree or higher from an accredited college or university in a quantitative discipline, such as:
- Statistics
- Mathematics
- Operations Research
- Engineering
- Computer Science
- Experience analyzing datasets and developing analytics.
- Experience programming with data analysis software such as:
- Python
- R
- SAS
- MATLAB
- Background in statistical analysis.
- Experience building, tuning, and testing predictive models.
- Experience creating analytic charts and dashboards.
- An additional two years of experience in software development, cloud development, dataset analysis, or developing descriptive, predictive, and prescriptive analytics may be substituted for a master's degree.
- A Ph.D. from an accredited college or university in a quantitative discipline may be substituted for four years of experience.
- Elasticsearch
- RegEx
- Machine learning
- Natural Language Processing
- Regression and predictive analysis
- Python
- MATLAB or R
- SQL or MongoDB
- Metric databases such as Grafana, Graphite, or InfluxDB
- ETL pipeline development
- Security and compliance data analysis
- Risk Management Framework knowledge
- Data quality validation
- Dashboarding and reporting
- Health, Dental, and Vision: Competitive plans with 100% paid premiums.
- 401(k): Company contributes 6%, even if you do not contribute.
- Paid Time Off: 11 standard holidays and 25 days of PTO.
- Career Development: Career counseling and individualized career development plans, including education and training support.
- Employee Referral Bonuses: Referral bonuses available for successful hires.
Ideal Candidate Profile The ideal candidate is an experienced cleared Data Scientist who enjoys working with complex datasets, building analytics, and using automation to improve security and compliance processes. This person should be comfortable working with Python, predictive models, ETL pipelines, dashboards, and security-related data to support continuous monitoring and RMF automation. Equal Opportunity Employer We are committed to fostering an inclusive workplace and welcome qualified applicants from all backgrounds. Employment decisions are based on qualifications, experience, clearance eligibility, and client requirements.
Vacancy posted 2 days ago
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