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VIVA USA Inc Machine Learning/Data Science Developer in Lemont, Illinois

Req Ref No: BTILID50 Location: Lemont , IL Duration: 11.0 months

Description

Scope:

Client is seeking to expand the capabilities of the new AIOps Center in BIS with advanced machine learning (ML) and data science experience. We require an additional resource to support ML model development, deployment, and post-production monitoring. The goal is to expedite growth in internal expertise in ML and more efficiently drive the AI for Operations projects in FY21. Common tasks to be performed include preparing datasets for ML modeling, design and optimize ML algorithms to accomplish business goals, run ML validations, tests, and experiments, analyze ML results, and deploy models to production application environments. This engagement will augment current technical resources in the AIOps Center to enable sufficient effort to deliver advanced AI/ML projects that will enhance existing and create new data-driven operations across the laboratory.

The ML Engineer will:

· Understand business objectives and develop models that help to achieve them, along with metrics to track their progress. · Research and implement appropriate machine learning algorithms and tools. · Supervise the data acquisition process and define data augmentation pipelines. · Study and transform data science prototypes into deployable solutions. · Design machine learning algorithms and systems. · Define validation strategies and run ML tests, analyses, and experiments that are statistically rigorous. · Develop and deploy machine learning applications that interface with models according to requirements. · Analyze errors in model output and design strategies to overcome them. · Monitor and evaluate the performance of deployed systems to ensure accuracy of results. · Document deployed processes and ML models, as well as the results of these models. · Participate in code reviews to ensure code quality and share best practices and experiences with the team. · Follow the latest developments in the field to be prepared to apply new techniques. · Complete all required client training. Computer Protection Program

The contractor shall adhere to all policies and procedures of the client Computer Protection Program, must not bypass any procedures established to protect data, applications, hardware, or communications at client, must maintain a work environment that will satisfy audit, privacy, and protection requirements, and must report any findings of inadequacies to the technical contact and the BIS Computer Protection Program Representative.

Qualifications:

· Comprehensive knowledge of Python. · Comprehensive knowledge of data structures, data modeling, and model evaluation. · Advanced knowledge of mathematics and data analytical skills. · Comprehensive knowledge of standard ML algorithms covering supervised learning, unsupervised learning, reinforcement learning, and deep learning. · Comprehensive knowledge of a broad range of data science and ML libraries (e.g., pandas and scikit-learn). · Proficiency with deep learning frameworks (e.g., TensorFlow, PyTorch, and Keras). · Working knowledge of git for distributed version control and CI/CD pipelines, as well as standard DevOps and MLOps processes. · Working knowledge of deploying solutions with Docker containers. · Familiarity with AutoML processes and ML platforms, such as Microsoft Azure and DataRobot a plus. · Comprehensive knowledge of SQL Server a plus. · Previous experience with Agile Scrum methodology a plus. · Considerable skill in defining and aligning team members to the common mission. · Able to work both independently and as a contributing member of a technical team. · Able to effectively interact with the organization to derive requirements and design solutions. · Able to disseminate knowledge to current staff.

VIVA is an equal opportunity employer. All qualified applicants have an equal opportunity for placement, and all employees have an equal opportunity to develop on the job. This means that VIVA will not discriminate against any employee or qualified applicant on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

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