Machine Learning Engineer - Boston, MA, United States - Aquent

Aquent Boston, MA, United States

Found in: Jooble US O C2 - 1 week ago

Description

Machine Learning Engineer (Security) | NFCUJP | Remote

be an intermediate-level position within the ML engineering field but will also require business soft skills
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

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 riskinformed 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
model input data, assumptions, and overall methodology leveraging supervised/unsupervised machine
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
Perform other duties as assigned
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 and dental insurance, life insurance, and eligibility to participate in 401k plan with company match

Qualifications

be an intermediate-level position within the ML engineering field but will also require business soft skills
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

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 riskinformed 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
model input data, assumptions, and overall methodology leveraging supervised/unsupervised machine
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
Perform other duties as assigned

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 and dental insurance, life insurance, and eligibility to participate in 401k plan with company match

Basic Purpose:
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 riskinformed decision making across the organization. Will operate under moderate supervision, but with
wide latitude for independent decision-making on project features, tuning, and presentation. This will
be an intermediate-level position within the ML engineering field but will also require business soft skills
and SQL/Database skillsets.
Responsibilities:

• 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. Analyze
model input data, assumptions, and overall methodology leveraging supervised/unsupervised machine
learning algorithms.

• 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
Desired Qualifications and Education Requirements:

• 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
Bank Secrecy Section (BSA):
Remains cognizant of and adheres to Navy Federal policies and procedures, regulations pertaining to the
Bank Secrecy Act.
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 and dental insurance, life insurance, and eligibility to participate in 401k plan with company match

Machine Learning Engineer - Boston, MA, United States - Aquent

Description

Responsibilities

Qualifications

Responsibilities

Benefits