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Computer and Information Science, Mathematics, Computer Engineering, Artificial Intelligence and Robotics, Statistics, Data Processing/Analytics/Science, Mathematical Statistics.
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Collaborating with software engineering teams to incorporate data science solutions into reusable software components; Staying current with the latest advancements in data science and machine learning.
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Demonstrating experience as a data scientist, with a focus on developing generative AI solutions; Understanding of how to develop and operationalize data science analytical models so these models can run in an automated context.
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Working knowledge of programming skills in Python, R, or similar languages, with experience in data manipulation, analysis, and modeling libraries (e.g. NumPy, Pandas, scikit-learn, TensorFlow, PyTorch.
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Understanding of ETL tools and techniques, like Azure Data Factory, Snaplogic Talend, Mapforce, etc. Understanding of machine learning algorithms (e.g. k-NN, GBM, Neural Networks Naive Bayes, SVM, and Decision Forests), statistical analysis, and data visualization techniques.
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Developing and implementing algorithms and models to solve business problems, (e.g. natural language processing, computer vision, and recommendation systems); Conducting exploratory data analysis to identify trends, outliers, and potential data quality issues.
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Designing and developing end-to-end generative AI solutions, from data collection and preprocessing to model training and deployment; Mentoring and providing guidance to junior data scientists and fostering a culture of continuous learning and growth.
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Understanding of how to map transformation and flow of data from a source to a target system; and, Problem-solving skills and the ability to translate business requirements into data-driven solutions.
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Leading, training, and working with other data scientists to design analytical approaches; We have skilled technologists, data scientists, product managers and business strategists who are using technology to accelerate change.
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Collaborating with cross-functional teams to understand business requirements and identify opportunities for leveraging data-driven solutions; Our team designs, develops and programs the methods, processes, and systems that are used to collect all forms of data and develop models that serve predictions to applications, automated process flows, and stakeholders.
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To help us achieve this we have the PwC Professional; our global leadership development framework. PwC is proud to be an affirmative action and equal opportunity employer. Our clients expect us to bring the right people and the right technology to solve their biggest problems; Products and Technology is here to help PwC meet that challenge and accelerate the growth of our business.
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All qualified applicants will receive consideration for employment at PwC without regard to race; creed; color; religion; national origin; sex; age; disability; sexual orientation; gender identity or expression; genetic predisposition or carrier status; veteran, marital, or citizenship status; or any other status protected by law.
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To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be an authentic and inclusive leader, at all grades/levels and in all lines of service.
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Utilizing experience with NLP and text-based extraction techniques; Working experience with deep learning frameworks and architectures (e.g. CNNs, RNNs, GANs); IFS - Information Technology (IT) Utilizing experience working with large-scale datasets and distributed computing frameworks (e.g. Hadoop, Spark), is a plus.
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Applying advanced statistical analysis and machine learning techniques to extract insights and patterns from complex datasets; As a Senior Manager, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution.
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computer science data scientist engineering jobs Company: Pwc in Kekaha, Hawaii
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