Data Science Engineer (TS/SCI) – ML & Compliance Analytics

J&T; Laurel (MD); On-site; USD 206,000 - 248,000; Full time

Benefits offered by this job

Health, Dental, Vision Insurance

Life Insurance

Disability Insurance

PTO and Holidays

401(k) with Company Match

Tuition Reimbursement

Job summary

J&T in Laurel, MD seeks an experienced Software Engineer (Level 2/3) to design, prototype, and enhance compliance analytics and business processing systems in an R&D setting. The role involves building automated tools, ML models, and data-driven features within a Linux environment.

You will collaborate with teams using Jira, Confluence, Git/GitLab, and Bitbucket, conduct EDA and feature engineering, and contribute to predictive model development, monitoring, and deployment.

Qualifications

• Bachelor’s degree in Computer Science or related discipline plus 14+ years of software engineering on similar programs.
• Alternatively, 18 years of relevant software engineering experience without a degree.
• Advanced development in Python, Java, and Scala on Linux.
• Experience with ML libraries (Scikit-learn) and data-processing tools.

Responsibilities

• Design and maintain compliance automation tools and analytics.
• Implement, test, and validate ML algorithms in an R&D environment.
• Conduct Exploratory Data Analysis and feature engineering on complex datasets.
• Build, deploy, and monitor ML models, data flows, and telemetry.
• Integrate distributed MapReduce processing workflows with backend pipelines.
• Develop full-stack and analytical software using Python, Java, Scala, SQL, JSON in Linux.

Skills

Python

Java

Scala

Machine Learning

Linux

Education

Bachelor’s degree in Computer Science or related discipline

14+ years of software engineering experience (with degree) or 18 years without a degree

Tools

Jira

Confluence

Git/GitLab

Bitbucket

Jupyter Notebooks

Job description

J&T in Laurel, MD seeks an experienced Software Engineer (Level 2/3) to design, prototype, and enhance compliance analytics and business processing systems in an R&D setting. The role involves building automated tools, ML models, and data-driven features within a Linux environment.

You will collaborate with teams using Jira, Confluence, Git/GitLab, and Bitbucket, conduct EDA and feature engineering, and contribute to predictive model development, monitoring, and deployment.