Responsible for researching, developing, and implementing Artificial Intelligence (AI) solutions to enable machines to simulate human intelligence by perceiving, reasoning, learning, and making decisions.
Locations (6)
Sioux Falls, South Dakota, United States
Phoenix, Arizona, United States
Louisville, Kentucky, United States
Troy, Michigan, United States
Franklin, Tennessee, United States
Easton, Pennsylvania, United States
Compensation
Salary range: $86,000 – $145,000. The salary range reflects the minimum and maximum target for a new hire in this role. Individual pay within the range will be determined by multiple factors which can include but are not limited to a candidate’s experience, qualifications, skills, and location. Your recruiter can share more about the specific salary for your location during the hiring process. Ranges may be modified in the future. This role is also eligible for an annual performance-based incentive opportunity.
Responsibilities
Research, design, and develop artificial intelligence and machine learning models to solve business challenges and enable machines to simulate human intelligence through perception, reasoning, learning, and decision-making capabilities.
Identify and evaluate opportunities for leveraging AI technologies across the organization, assess existing workflows, and recommend AI-driven solutions that improve efficiency, accuracy, and business outcomes.
Collect, prepare, and preprocess data from various sources for model training, including data cleaning, feature engineering, exploratory analysis, and establishing data pipelines to support continuous improvement.
Train, validate, and optimize AI models using appropriate algorithms, frameworks, and evaluation metrics to ensure robustness, performance, and accuracy while mitigating biases and ensuring ethical AI practices.
Integrate AI solutions into existing systems, applications, and workflows by developing APIs, microservices, or interfaces that enable seamless deployment and scalability in production environments.
Associate focused on enabling digital and AI solutions for customer-facing teams across Europe, primarily based in Munich with occasional travel within Europe.
Locations (2)
Munich, Bavaria, Germany
Garching, Bavaria, Germany
Responsibilities
Engage with customer-facing teams to identify improvement opportunities
Translate business needs into digital and AI use cases
Build and test prototypes using Python, SQL, and machine learning
Use operational data to improve transparency and decision support
Re-architect processes to reduce manual work
Requirements
Master's degree or equivalent in industrial engineering, data science, computer science, artificial intelligence, machine learning, operations research, business analytics, or related discipline
Nice to have: Microsoft Fabric
Nice to have: Power BI
Nice to have: data quality improvement
Stage Analyse des données et modélisation du vieillissement des batteries Bac+5 (H/F)
The Cardiac Technician assists nursing staff in monitoring heart rhythms of patients on telemetry, interprets dysrhythmias, performs electrocardiographs, and manages clerical operations of the EKG area.
Responsibilities
Monitor heart rhythms on telemetry
Interpret dysrhythmias and notify nursing staff
Perform electrocardiographs in Non-Invasive Cardiology
Prepare data for physician interpretation
Transcribe, file, and report EKG results
Requirements
High School diploma or equivalent
Nice to have: Prior training in EKG rhythm strip interpretation
Lead data analysis, modeling, integration, and program management within the Insights, Data Engineering & Analytics organization.
Compensation
Starting base salary: $77,000 - $143,000 per year. Exact compensation may vary based on skills, experience, and location. This job is eligible for bonus and/or commissions.
Responsibilities
Lead data analysis via data discovery, exploration, investigation, and impact assessments
Conduct and lead data profiling and preparation
Validate data against requirements
Model data with ER diagrams and data flow diagrams
Research business processes and document inconsistencies
Contribute to the design and deployment of data initiatives that deliver accurate, timely, and actionable insights for decision making.
Compensation
The expected annual salary range for this position based on the primary location for this position of Oceanside, California is $160,992 to $180,600 per year. Actual pay within the range will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance.
Responsibilities
Design and deploy data initiatives
Improve digital performance management tools
Own lifecycle management of Digital Performance Management tools
Translate operational priorities into performance measures
Collect, validate, and analyze operational, quality, and delivery data
Requirements
Bachelor’s degree in Science, Engineering, or Data Analytics
Develops, interprets, and implements statistical, financial, and accounting concepts and quantitative techniques to support credit risk modeling, financial forecasting, model monitoring, and reporting.
Responsibilities
Apply statistical theory, econometric methods, and quantitative techniques to collect, organize, validate, interpret, and summarize numerical and text data to provide usable information.
Interpret quantitative data and design statistical models for researching problems or questions.
Perform data analysis using statistical programming software such as Python, R, or SAS, with emphasis on accuracy, reproducibility, data quality, and effective analytical controls.
Analyze and interpret data to identify trends, patterns, anomalies, and emerging risks that may affect performance, model results, or estimates.
Develop and maintain analytical programs, reusable scripts, data validation routines, and automated workflows that improve the efficiency and consistency of quantitative processes.
Requirements
Bachelor's degree in Statistics, Mathematics, Mathematics, or Economics with a strong quantitative concentration, Data Science, or another closely related quantitative discipline.
Master's degree in Statistics, Mathematics, Economics, or Data Science
Support the John Deere Financial Global Fraud team by maintaining, validating, and enhancing risk-based analytical models and providing analytical support across other domains within the GOA team.
Responsibilities
Maintain, assess, validate, and enhance risk-based models supporting Global Fraud detection, operational prioritization, and decision making
Develop and apply analytical models and methods to address evolving fraud risks and business needs
Analyze data to identify patterns, anomalies, emerging risks, and opportunities to improve model effectiveness
Partner with Global Fraud, GOA leadership, and other business and technical stakeholders to understand business questions, define analytical requirements, and establish measures of success
Build and maintain repeatable data preparation, testing, model assessment, and validation processes
Requirements
Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Finance, Analytics, or a related quantitative field
Lead complex AI/ML initiatives, design, develop, evaluate, and operationalize enterprise AI solutions, mentor junior data scientists, and collaborate across engineering and product teams.
Compensation
The range listed is just one component of BMC's employee compensation package. The annual base salary range represents the low and high end of the BMC salary range for this position. Actual salaries depend on a wide range of factors that are considered in making compensation decisions, including but not limited to skill sets; experience and training, licensure, and certifications; other business and organizational needs. The range listed is zł 251,025 - zł 418,375
Responsibilities
Design and develop AI/ML solutions
Evaluate and operationalize models
Mentor junior data scientists
Collaborate with AI Engineering and Platform Engineering
Lead technical decisions
Requirements
Bachelor’s degree in Machine Learning, Statistics, Data Science, Physics, Computer Science, or a related field
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