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Algorithm Development (25%) Implement machine learning, statistical, data-mining, bioinformatics/clinical informatics algorithms. Design, setup and run computational experiments to evaluate and benchmark cutting-edge machine learning algorithms.
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AMP Robotics is hiring a Sr Machine Learning Engineer, In this role, you would be an individual contributor on our deep learning modeling team, working on research and development projects to help us implement state of the art deep learning techniques.
ExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Whether you join our Statistics, Optimization, Advanced Algorithms or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Search, Personalization, GenAI, Marketing, Supply Chain Optimization, Network Security rely on.
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Using a Premium Audit selection model, the team can predict the likelihood of policy misclassification, automatically assign audit methods to save carriers time and money, and use machine learning to continuously improve correlation and prediction accuracy.
ExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Knowledge of machine learning, statistical modeling and optimization, some experience working directly or indirectly in Python or R. Our rotational experience is designed to accelerate your learning and growth as you work towards a potential promotion by program graduation.
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Whether you join our Statistics, Optimization or Machine Learning teams, you’ll be challenged to harness Target’s impressive data breadth to build the algorithms that power solutions our partners in Marketing, Supply Chain Optimization, Search and Personalization rely on.
ExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Continue to develop and help drive the strategy for the organization's data strategy including data architecture, Reporting, Insights, Analytics, Operations, Predictive modeling, attribution and Machine Learning/AI.
ExpandApply NowActive JobUpdated 11 days ago - UpvoteDownvoteShare Job
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Stochastic Modeling, Optimization, Simulation, Computational Statistics, and Machine Learning. Predictive modeling using statistical and machine learning techniques.
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Experience with machine learning algorithms and predictive modeling. Provides mentorship and guidance to others, fostering a culture of continuous learning and development within the team.
Full-timeRemoteExpandApply NowActive JobUpdated 25 days ago - UpvoteDownvoteShare Job
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SDS has also invested meaningfully in automation and machine learning capabilities across its tech-enabled processes to drive scalability and greater internal operating efficiency while also improving client results.
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Use your coding knowledge to partner with Data Science in the machine-learning model/tool-development process, work on data retrieval and support our model-automation process using VBA tools.
Full-timeExpandApply NowActive JobUpdated 25 days ago - UpvoteDownvoteShare Job
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Execute predictive and inferential analytics, machine learning, and artificial intelligence techniques. The Data Scientist Senior thrives when constructing complex solutions that integrate data wrangling, visualization, and advanced modeling techniques into a seamless workflow using software development best practices in R, Python, or other scripting languages.
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Experience with machine learning, statistical modeling, predictive modeling are imperative; text mining and topic modeling are plus. unsupervised machine learning, clustering, ensemble methods, etc.
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Every scientist on Target’s Data Sciences team can expect to do modeling and data science, develop software/product with highly performant code, elevate Target’s culture, and apply retail domain knowledge.
ExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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Research, design, and test computational environments to support analytical modeling (statistics, machine learning, optimization, and simulation) Minimum of 5 years experience working with Microsoft BI Tools including Azure Data Lake, Azure Data Lake Analytics, Azure SQL Database, Data Bricks and Azure SQL Data warehouse and Azure Data Factory.
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modeling machine learning jobs in Minneapolis, MN
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As the job market remains highly competitive, we have seen a surge in "rage applying." This is when candidates apply to multiple jobs, often without considering whether they are truly interested in the role. Rage applying goes hand-in-hand with quiet quitting. Often, employees want to entertain the thoughts and feelings of leaving their job, but they aren't necessarily serious about leaving yet. Meanwhile, other employees engaging in this trend are actually trying to find a better role. As a recruiter, it can be hard to identify who are the real applicants in a sea full of quiet quitters, but understanding rage applying and identifying red flags will certainly help.
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Building a candidate pipeline through a great internship program for local college students and recent graduates at local universities is a great and cost-effective way to attract and retain top talent. By offering meaningful and impactful work experiences, regular feedback, coaching, and mentorship, you can create a positive internship experience that will make your organization a sought-after destination for future employees. This not only benefits the organization in the short-term but also in the long-term, as you'll have a pool of well-trained and experienced candidates who may be interested in full-time employment once they graduate. Furthermore, building relationships with local universities and college students can increase brand awareness and build a positive reputation for your organization in the local community.
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Transparency in hiring refers to the open and honest communication and information sharing that takes place between employers and job candidates. It encompasses all aspects of the hiring process, from posting job descriptions to providing feedback on performance during and after the interview process. In today's job market, hiring transparency has become increasingly important for both employers and candidates alike.