Cybersecurity Data Scientist - TS/SCI Clearance

Parsons

Maryland

On-site

USD 112,000 - 196,000

Full time

3 days ago

Be an early applicant

Application generator

Stand out for this role — generate a tailored resume and cover letter in about a minute.

Get past ATS filters

Job summary

Parsons is seeking a Senior Data Scientist in Maryland to support defense cybersecurity analytics. You will develop ML and statistical models, structure diverse data sources, and craft visualizations for technical and non-technical stakeholders.

You will collaborate with engineers, analysts, and cloud teams to productionize analytics within a federal solutions context. The role requires TS/SCI with Polygraph, 7+ years of experience, and expertise across Python, R, SQL, and big data tools.

Qualifications

Active TS/SCI security clearance with Polygraph.
Bachelor degree, with additional years of experience able to count in lieu of a degree.
7+ years of experience, with additional education able to count towards total years of experience.
Experience with designing/implementing machine learning, data mining, advanced analytical algorithms, advanced statistical analysis, artificial intelligence, or software engineering with data analysis software (R, Python, SAS, MATLAB).
Experience with Windows server management and Power BI Report Service.
Proficiency with Python/Jupyter Notebooks, SQL and relational databases, ElasticSearch/Kibana/OpenSearch. Experience with Java is also a plus.
Background working with analyst teams including conducting data analysis and creating data visualizations. Experience with graph analytics, data pipelines, and IP-based network data is a plus, but not required.
Experience working within a cybersecurity mission environment using tools and capabilities to generate threat intelligence.

Responsibilities

Develop statistical, and graph-based algorithms to analyze and make sense of data sets.
Clean and structure disparate data received from a globally dispersed customer base.
Provide insight into dataset structures and produce data visualizations that are consumable by both technical an non-technical audiences.
Translate mission customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes.
Develop and implement statistical, and machine learning techniques to create descriptive and predictive analytics.
Evaluate and validate the performance of analytics using standard techniques and metrics and oversee development of individual analytic development efforts guiding them toward solutions that can scale to large datasets.
Work in close partnership with subject matter experts, software engineers, and cloud developers to guide the formulation of analytics to production.