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Masters degree in Computer Science, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning. Bachelor's degree in Computer Science, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning.
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2 years of experience must include: Python; R; SQL; Hive; Tableau; Statistical modeling: linear and logistic regression; Machine learning techniques: Support Vector Machines and Random Forrest; and Exploratory and advanced data analytics.
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Expert level in Designing and Architect solutions in Azure Data factory, Azure Databricks, Azure Datalake, Delta Lake and Azure synapse analytics implementation. We provide strategic and technical advice, and we have expertise in areas covering Artificial Intelligence, Cloud Migration, Custom Software Development, Data Analytics Infrastructure & Cloud Solutions, Cyber Security Services, etc.
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Design, develop, and implement machine learning models and algorithms to solve complex problems across various domains, including but not limited to recommendation systems, natural language processing, and predictive analytics.
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Techniques: Statistical Analysis, Visualization, Optimization, Machine Learning, Big Data, Data Warehouse, NLP. Drive the adoption of data science-driven mechanisms and machine learning models to continuously evaluate and improve catalog data quality.
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Experience in mathematics (statistics, linear algebra, differential calculus); data visualization (Tableau, Power BI, Qlikview); programming (SQL, Python, R, Java); data analysis (feature engineering, data wrangling, EDA) and machine learning (classification, regression, reinforcement learning, deep learning, clustering, dimensionality reduction.
$113,200 - $205,500 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Integrating innovative approaches to individual and team work products such as machine learning, artificial intelligence, data mining, predictive modeling, neural networks and simulation to mitigate price/value leakage across the pursuit and delivery phases of an engagement.
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Mentor and support a diverse virtual global team of business intelligence and data analytics professionals in support of consistently delivering innovative and timely insights that integrate storytelling to influence without authority.
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A University/Bachelor’s Degree, STEM, Economics, Data Science or Analytics preferred. Strategic Pricing & Insights (SPI) group: Data and Analytics Assistant Director. 6+ years of experience in analytics, data science, and development of complex pricing models.
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A successful Data and Analytics Assistant Director delivers exceptional client service by building insights ahead of the market, creating innovative, compelling and differentiated perspectives, positioning EY to win more, win bigger, win better.
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Enhancing data handling, data hygiene, data cleaning and data modeling methods to connect structured and unstructured data using Python, R, Power Platform, SharePoint and Excel to uncover market performance improvement opportunities.
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Executing the data engineering strategy to allow for a scalable and reliable data architecture supporting multiple platforms considering data ingestion, transformation, and storage; supported with detailed documentation and maintenance of processes, methods and procedures including Python and SQL codes.
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Analytical skills with hands-on experience developing or validating predictive machine learning models on data sets in Hadoop/AWS environments using Python, R. and SAS. Familiarity with or understanding of Anti Money Laundering, Market/Trade Surveillance, Artificial Intelligence/Machine Learning and decision trees & cluster analysis.
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Data Science and Machine Learning Frameworks Apache Spark / MLlib, TensorFlow, Scikit-learn, etc. Utilizing knowledge of data science and machine learning frameworks including PyTorch, Keras, TensorFlow, and Scikit-learn; natural language processing including generative AI LLMs, NLTK, Spacy; and cloud platforms including AWS and Azure in the performance of job duties.
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Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Advanced Analytics - Applied Econometrics, Advanced Calculus, Statistical Methods, Data Visualization, Decision Analytics & Optimization, ML, Big Data, Social Network Analytics.
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