Aquent
Machine Learning Engineer (Security) | NFCUJP00012078 | Remote
Aquent, Boston, Massachusetts, us, 02298
Machine Learning Engineer (Security) | NFCUJP00012078 | Remote
Responsibilities
Using data science and machine learning analytics, the contractor will develop models and insights to support risk-based operational decisions for the organization. Will work collaboratively with multiple departments to develop data pipelines for ML modeling and process optimization. Will be tasked with creating descriptive and predictive models in conjunction with cybersecurity frameworks to drive risk-informed decision making across the organization. Will operate under moderate supervision, but with wide latitude for independent decision-making on project features, tuning, and presentation. Support the delivery of strategic advanced analytics solutions across the organization with solutions drawing on descriptive and predictive modeling, with a focus on ML engineering. Leverage a broad set of modern technologies – including Python, R, Scala, and SQL – to analyze and gain insights within large data sets. Evaluate model design and performance and perform feature analysis and hyper tuning. Using statistical practices, analyze current and historical data to make predictions, identify risks, and opportunities, enabling risk-informed decision making. Collaborate with other team members, subject matter experts, pods, and delivery teams to deliver strategic advanced analytic based solutions from design to deployment. Recognize potential issues and risks during project implementation and suggest mitigation strategies. Perform other duties as assigned. Qualifications
Master’s degree in Statistics, Mathematics, Computer Science, Engineering or other related fields. Familiarity with Cloud computing environments such as Microsoft Azure. Familiarity and/or willing to learn deep learning capabilities leveraging Tensorflow/Torch. Familiar with project management concepts and frameworks, and tools such as ADO. Communication Strategy and Management, Delivery Excellence and Requirements management. Benefits
The target hiring compensation range for this role is the equivalent of $65.45 to $72.72 an hour. Compensation is based on several factors including, but not limited to education, relevant work experience, relevant certifications, and location. Additional benefits offered may include medical health insurance, dental insurance, life insurance, and eligibility to participate in 401k plan with company match.
#J-18808-Ljbffr
Using data science and machine learning analytics, the contractor will develop models and insights to support risk-based operational decisions for the organization. Will work collaboratively with multiple departments to develop data pipelines for ML modeling and process optimization. Will be tasked with creating descriptive and predictive models in conjunction with cybersecurity frameworks to drive risk-informed decision making across the organization. Will operate under moderate supervision, but with wide latitude for independent decision-making on project features, tuning, and presentation. Support the delivery of strategic advanced analytics solutions across the organization with solutions drawing on descriptive and predictive modeling, with a focus on ML engineering. Leverage a broad set of modern technologies – including Python, R, Scala, and SQL – to analyze and gain insights within large data sets. Evaluate model design and performance and perform feature analysis and hyper tuning. Using statistical practices, analyze current and historical data to make predictions, identify risks, and opportunities, enabling risk-informed decision making. Collaborate with other team members, subject matter experts, pods, and delivery teams to deliver strategic advanced analytic based solutions from design to deployment. Recognize potential issues and risks during project implementation and suggest mitigation strategies. Perform other duties as assigned. Qualifications
Master’s degree in Statistics, Mathematics, Computer Science, Engineering or other related fields. Familiarity with Cloud computing environments such as Microsoft Azure. Familiarity and/or willing to learn deep learning capabilities leveraging Tensorflow/Torch. Familiar with project management concepts and frameworks, and tools such as ADO. Communication Strategy and Management, Delivery Excellence and Requirements management. Benefits
The target hiring compensation range for this role is the equivalent of $65.45 to $72.72 an hour. Compensation is based on several factors including, but not limited to education, relevant work experience, relevant certifications, and location. Additional benefits offered may include medical health insurance, dental insurance, life insurance, and eligibility to participate in 401k plan with company match.
#J-18808-Ljbffr