Machine Learning Engineer- Cerner/Epic Remote 12+ months

Remote Full-time
Machine Learning Engineer - Cerner/Epic Remote 12+ months This Jobot Consulting Job is hosted by Robert Reyes. Are you a fit? Easy Apply now by clicking the Easy Apply button and sending us your resume. Salary: $85,000 - $194,000 per year A Bit About Us: 100% Remote 12+ month remote contract. Looking for a strong Machine Learning Engineer - Cerner/Epic Remote 12+ months. Apply today to learn more about this consulting role. Why join us? 100% Remote 12+ month remote contract Competitive W2 or C2C contract rates Work with a high-performing team within a leading HIT setting Competitive Salary Stellar Benefits (Medical, Dental Vision, Life Insurance) Flexible Schedule Job Stability Career growth If you are passionate, thrive in a fast-paced environment, and are ready to take your career to the next level, we would love to hear from you. Job Details: We are currently seeking a dynamic and innovative Consulting Machine Learning Engineer with expertise in Cerner/Epic for an exciting remote position. This role is a 12+ month contract in the Tech Services industry. The ideal candidate will have a strong background in machine learning, data analysis, and predictive modeling, along with a deep understanding of Epic or Cerner systems. With a minimum of 5 years of experience in the field, you will have the opportunity to collaborate with a team of passionate professionals, helping to drive the future of healthcare technology. Responsibilities: Design, develop, and implement machine learning models and algorithms to solve complex healthcare problems. Leverage your knowledge of Cerner/Epic systems to extract and analyze data, and provide insights to improve patient care and operational efficiency. Collaborate with cross-functional teams to understand their business needs and develop data-driven solutions. Conduct research on the latest machine learning and artificial intelligence trends, and propose innovative ideas to enhance our current systems. Create clear and concise documentation for machine learning models, and provide training and support to other team members. Work closely with the data engineering team to build and maintain robust data pipelines. Participate in code reviews to ensure the quality and scalability of the codebase. Utilize your strong problem-solving skills to troubleshoot and resolve any issues that may arise. Qualifications: Bachelor's degree in Computer Science, Data Science, Engineering, or a related field. A Master's degree or PhD is highly desirable. Minimum of 5 years of experience in machine learning, data analysis, and predictive modeling. Proven experience with Cerner/Epic systems is a must. Strong programming skills in Python, R, or other relevant languages. Familiarity with machine learning frameworks such as TensorFlow, Keras, or PyTorch. Excellent understanding of machine learning algorithms, data structures, and performance optimization techniques. Experience with cloud platforms like AWS, Google Cloud, or Azure. Strong written and verbal communication skills, with the ability to explain complex concepts to non-technical stakeholders. Self-motivated, with a passion for learning and staying up-to-date with the latest technologies in the field. Ability to work independently and as part of a team, managing multiple tasks and projects simultaneously. Previous experience in the healthcare industry is a plus. If you are a passionate and innovative Consulting Machine Learning Engineer with a desire to make a significant impact in the healthcare industry, we would love to hear from you. Jobot is an Equal Opportunity Employer. We provide an inclusive work environment that celebrates diversity and all qualified candidates receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. #J-18808-Ljbffr Jobot Consulting Apply tot his job Apply tot his job Apply tot his job
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