Senior Machine Learning Scientist - Garden City, United States - Cambia Health
Description
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Cambia Health
Senior Machine Learning Scientist - R-4927_ _2-4185
in
Boise ,
Idaho
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Senior Machine Learning Scientist
Remote or Hybrid within OR, WA, ID or UT
Cambia Health Solutions is working to create a seamless andfrictionless healthcare experience for consumers nationwide.
Thispresents a unique challenge and opportunity for innovative solutionsthat serve patients and providers and influence the healthcare system.
Cambia\'s AI team builds, prototypes, and deploys data-driven models andalgorithms to production systems, delivering more equitable, effective,and affordable health care to our members.
We are seeking a highly-skilled and experienced Senior Machine LearningEngineer to join us and help advance our current and future workapplying machine learning, deep learning, and NLP to deliver betterhealth care.
We contribute broadly across Cambia, working on a widerange of challenging problems, for instance:Reducing our members\' claim costs using both supervised andunsupervised approaches.
Speeding up prior authorizations and appeals using NLP to understandclinical notes.
Personalizing member engagement to promote the health and well-beingof our members.
Driving health equity across Cambia initiatives.
And much more
As a Senior ML Engineer on our team, you will play a crucial role inidentifying gaps in our existing ML platform and architecting andbuilding solutions to address those gaps.
You will also collaborate withthe AI team\'s ML Scientists and our partner data engineering andsoftware development teams to bring ML models to production and maintaintheir health and integrity while in production.
Your expertise inmachine learning, coupled with a strong background in softwaredevelopment, will be instrumental in driving the success of Cambia\'sAI/ML initiatives.
Qualifications and Requirements:
Academic degree
(Masters or PhD preferred) in Computer Science,Engineering, or a related field.
Minimum of 7 years of experience
in ML development and deployingML solutions in cloud-based production environments.
Experience with ML platforms and ML Ops : Demonstrated experiencein assessing and improving ML platforms, identifying gaps, andarchitecting solutions to address them.
Strong familiarity with MLplatform components such as data ingestion, preprocessing, featurestores, model training, deployment, and monitoring.Strong machine learning expertise :
Proficient in machinelearning algorithms, statistical modeling, and data analysis.
Hands-on experience with standard ML frameworks (e.g., TensorFlow,PyTorch) and libraries (e.g., scikit-learn, XGBoost).
Software development skills :
Solid understanding of softwareengineering principles, data structures, and algorithms. Proficientin Python and/or other programming languages commonly used in MLdevelopment.
Data preprocessing :
Proficient in SQL and/or pythondata-processing libraries such as pandas, NumPy, etc.
Collaborative mindset :
Ability to work effectively withcross-functional teams to drive alignment and deliver high-qualitysolutions. Strong communication and collaboration skills areessential.
Problem-solving and analytical thinking : Ability to analyzecomplex problems, break them down into manageable components, andpropose innovative solutions. Strong analytical skills forevaluating system performance, identifying bottlenecks, andimplementing optimizations.
Continuous learning :
Passion for staying up-to-date with thelatest advancements in machine learning and data engineering.
Proactive in learning new tools, techniques, and frameworks to driveinnovation and improve the ML platform.
Healthcare knowl dge :
Previous experience is beneficial but notrequired.
Responsibilities:
ML platform and ML Ops : Identify areas that require improvements oradditional functionalities and use your expertise in machine learningand software engineering to architect and develop solutions that fillgaps in our ML platform and development ecosystem.
System scalability and reliability :
Optimize the scalability,performance, and reliability and AI Team solutions by implementing bestpractices and leveraging industry-standard technologies. Collaboratewith infrastructure teams to ensure smooth integration and deployment ofML solutions. Design scalable and efficient systems that leverage thepower of machine learning for enhanced performance and capabilities.
Data processing and workflow pipelines : Streamline data ingestion,preprocessing, feature engineering, and model training workflows toimprove efficiency and reduce latency.
Work with data engineering anddata platform teams to design and implement robust data pipelines thatsupport the AI team\'s needs.#J-18808-Ljbffr