Data Science Engineer for Cybersecurity & Power Systems

Lawrence Livermore National Laboratory; Livermore (CA); Hybrid; USD 146,340 - 222,564; Full time

Benefits offered by this job

Flexible Benefits Package

401(k)

Relocation Assistance

Education Reimbursement Program

Flexible schedules depending on project needs

Job summary

A laboratory specializing in national security and technology is seeking a Data Science Engineer to develop and apply machine learning algorithms for cybersecurity and power systems. The role involves collaborating with diverse teams and requires a Bachelor's degree in a relevant field with strong Python skills. Positions offer a hybrid schedule with flexible working options and competitive salary ranging from $146,340 to $222,564 annually, based on experience and role level.

Qualifications

• Secure and maintain a U.S. DOE Q-level security clearance.
• Combine education and related experience effectively.
• Experience applying data science methods to practical challenges.

Responsibilities

• Design and develop machine learning algorithms for critical infrastructure.
• Write code and deploy data science solutions effectively.
• Collaborate with multidisciplinary teams to foster innovation.

Skills

Python programming

Machine learning

Deep learning

Data visualization

Software engineering best practices

Communication skills

Interpersonal skills

Education

Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field

Tools

TensorFlow

PyTorch

scikit-learn

Keras

Job description

A laboratory specializing in national security and technology is seeking a Data Science Engineer to develop and apply machine learning algorithms for cybersecurity and power systems. The role involves collaborating with diverse teams and requires a Bachelor's degree in a relevant field with strong Python skills. Positions offer a hybrid schedule with flexible working options and competitive salary ranging from $146,340 to $222,564 annually, based on experience and role level.