Cybersecurity Engineer

gdit; United States; Hybrid; USD 140,000 - 170,000; Full time

Job summary

gdit is seeking a seasoned data science leader to develop advanced analytics for cybersecurity threats and fraud patterns across large datasets. You will build AI/ML solutions, support security operations, and translate analysis into practical recommendations to improve systems and processes.

You will work with Python, SQL, R, and Databricks on cloud platforms, collect and integrate new data sources, respond to investigations, and guide cross-functional teams to deliver secure analytics while

Qualifications

• Eight or more years of relevant experience and a bachelor’s degree in engineering, IT, security, or a related field; equivalent experience may qualify, with additional experience required in place of a relevant degree.
• Expert knowledge of data science, AI/ML, and fraud detection, including solution design and delivery.
• Strong experience with Python, SQL, R, and a cloud analytics platform such as Databricks.
• Knowledge of data strategy and governance, model lifecycle management, analytics architecture, and secure technology implementation.
• Ability to engage stakeholders, coordinate specialized teams, and deliver across multiple concurrent initiatives.
• Ability to obtain and maintain a public trust clearance and meet the stated U.S. residency requirements.

Responsibilities

• Use data science and AI/ML methods to detect threats and potential fraud across data from multiple sources.
• Build, evaluate, and maintain analytical solutions using Python, SQL, R, and a cloud-based data platform.
• Collect, combine, and analyze new data sources with teams across the organization to speed delivery of useful insights.
• Respond to ad hoc investigations and explain complex findings to technical and business stakeholders.
• Identify gaps in systems and processes, then recommend remediation to reduce security and fraud risks.
• Guide specialist teams delivering analytics, business intelligence, and AI solutions across secure environments.

Skills

Data science

AI/ML

Fraud detection

Stakeholder engagement

Education

Bachelor’s degree in engineering, IT, security, or related field

Tools

Python

SQL

R

Databricks

Job description

Role overview

Develop advanced analytics to identify cybersecurity threats and fraud patterns in large, varied datasets. The role supports security operations by building AI and machine learning solutions, responding to stakeholder investigations, and turning analysis into practical recommendations for improving systems and processes.

Responsibilities

• Use data science and AI/ML methods to detect threats and potential fraud across data from multiple sources.
• Build, evaluate, and maintain analytical solutions using Python, SQL, R, and a cloud-based data platform.
• Collect, combine, and analyze new data sources with teams across the organization to speed delivery of useful insights.
• Respond to ad hoc investigations and explain complex findings to technical and business stakeholders.
• Identify gaps in systems and processes, then recommend remediation to reduce security and fraud risks.
• Guide specialist teams delivering analytics, business intelligence, and AI solutions across secure environments.

Requirements

• Eight or more years of relevant experience and a bachelor’s degree in engineering, IT, security, or a related field; equivalent experience may qualify, with additional experience required in place of a relevant degree.
• Expert knowledge of data science, AI/ML, and fraud detection, including solution design and delivery.
• Strong experience with Python, SQL, R, and a cloud analytics platform such as Databricks.
• Knowledge of data strategy and governance, model lifecycle management, analytics architecture, and secure technology implementation.
• Ability to engage stakeholders, coordinate specialized teams, and deliver across multiple concurrent initiatives.
• Ability to obtain and maintain a public trust clearance and meet the stated U.S. residency requirements.

Nice to have

• Experience with Tableau, AWS, large language models, computer vision, or MLOps.

Benefits and work setup

• Remote work is available, with listed office locations in North Carolina, Virginia, and Minnesota.
• Benefits include a retirement plan with employer match, health and wellness coverage, paid vacation and holidays, and support for professional development and certifications.