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You have passion and expertise in one or more of the following areas: risk analytics, data analytics, machine learning, SQL, Python, cloud security, network security, vulnerability management, data protection, threat intelligence & investigations, and identity & access management.
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Experience leveraging complex data to drive business decisions, hands on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Pytong, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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As a candidate for this role, you’re able to seamlessly switch from executive-level risk conversations to diving deep into controls and technology to driving high level, strategic discussions around metrics, data, and risk analytic reporting solutions.
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Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.
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You have experience working with large data sets and have either used or are interested in learning dbt and Python. Analyze internal and external data to gain a deep understanding of our Ideal Customer Profile (ICP) and help identify accounts that meet this criteria.
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Strong expertise in NLP/NLU with focus on deep learning models and open source LLMs such as Llama 2, Falcon etc., · Proficiency in programming languages such as Python and experience with NLP. libraries/frameworks like spaCy, NLTK, Hugging Face Transformers and Generative AI and LLM frameworks.
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To accelerate our customers transformation leveraging cloud, we combine world-class learning and talent development expertise; deep experience in cloud change management; and cloud-ready operating models with a commitment to responsible business by design — with security, data privacy, responsible use of artificial intelligence, sustainability and ethics and compliance built into the fundamental changes Accenture helps companies achieve.
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Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data.
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Deep knowledge of machine learning, predictive analytics, and statistical modeling techniques, with proficiency in data science tools and programming languages such as Python, R, or Scala.
$175,000 - $225,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Visualizing data using a diverse tool set including but not limited to Python and R. Database Management System: Knowledge of how to work with data from (do not build)SQL skills (relational) - CORE / Initial ProficiencyUnstructured (NoSQL)Graph / ontology (DB Graph)Data Analysis and Insights: Analyzing structured and unstructured data using data visualization, manipulation, and statistical methods to identify patterns, anomalies, relationships, and trends.
$173,500 - $234,700 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Our data science track covers most of the below: Topics and content might change based on the market requirements Python NumPy and Pandas Matplotlib data visualization Difference between Machine learning, Artificial Intelligence and Deep learning Data Manipulation: Cleansing-Munging Data Analysis.
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Basic knowledge and experience in statistical and data mining techniques such as: generalized linear model (GLM)/regression, random forest, boosting, trees, text mining, hierarchical clustering, deep learning, convolutional neural network (CNN), recurrent neural network (RNN), T-distributed Stochastic Neighbor Embedding (t-SNE), graph analysis, etc.
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With PySpark, Python, SQL, Excel, and data visualization tools (Tableau, Power BI, etc.) of machine/deep learning techniques and algorithms (XGBoost, random forests, logistic regression, SVM, KNN, k-means clustering, PCA, neural network, deep reinforcement learning, etc.
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Experience with Python and it's deep learning frameworks. Advanced degree in Machine Learning, Data Science, or similarly related field. This candidate will have experience deploying Machine Learning and AI models into production environments.
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This role is pivotal in leveraging Data and AI technologies, requiring a deep understanding of Data Science, Statistics, Machine Learning, Generative AI, Large Language Models (LLMs), and Multimodal models.
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