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Cloud Computing – Use the full range of Microsoft Azure Services with exposure to machine learning. Using tools such as SQL, DataBricks, Talend, Python, Microsoft Power Platform and Azure Data Factory.
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Utilize programming languages like JavaScript, Java, HTML/CSS, TypeScript, SQL, Python, and Go, Open Source RDBMS and NoSQL databases, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services.
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We are working on challenging projects, migrating ETL jobs from Talend to DataBricks, building workflow automation solutions using Microsoft Power Platform, data flows with Azure data lake storage and DevOps environment set up.
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2+ years of experience with OpenSearch, Kafka, Vue.js and some exposure to Machine Learning. 7+ years of experience in at least one of the following: JavaScript, Java, TypeScript, SQL, Python, or Go.
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Statistical and machine learning techniques for analyzing financial data, including survival analysis, time series analysis, GLM, logistic regression, XGboost, LightGBM, Random Forest, Neural Networks, decision tree analysis, and cluster analyses.
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Proficiency in analytical software and tools including Python, SAS, R, SQL and other applications, such as Microsoft Excel/VBA and Access; Demonstrating proficiency in analytical software and tools including Python, SAS, R, SQL and other applications, such as Microsoft Excel/VBA and Access.
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As a Senior Machine Learning Engineer, you will work on building AI/ML solutions across a wide range of business applications. Strong programming skills in Python and Java; experience with Machine Learning libraries and frameworks.
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Applying expertise in multiple modeling methodologies including survival analysis, transition rate modeling, time series analysis, credit scoring, Monte Carlo simulation, Artificial Intelligence/Machine Learning techniques such as neural networks and tree based algorithms etc.
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Econometric/statistical, machine learning, and other analytical modeling; Identifying and addressing client needs, including building solid client relationships, developing an awareness of Firm services, and technological advances in the industry.
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Strong proficiency in programming (e.g., SQL, Python, R, MATLAB), database technologies (Oracle, mySQL, relational databases; graph databases are a plus), machine learning/deep learning (network architectures are a plus), dimensionality reduction techniques (e.g., PCA), and possible cheminformatics software suites.
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Lead a portfolio of diverse technology projects and a team of developers with deep experience in distributed microservices, and full stack systems to create solutions that help meet regulatory needs for the company.
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We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge. As part of our team, you'll help our clients implement enterprise content and data management applications that improve operational effectiveness and provide impactful data analytics and insights.
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The Research Data Scientist participates in biomedical research projects using programming, data-mining, statistics, machine learning, and visualization techniques to develop, evaluate, and/or apply algorithms and software for data analysis.
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Machine Learning | Physics | Embedded Systems | Signal Processing | Data Analysis | Nvidia | Electrical Engineering | Cloud Computing | Cuda | TensorRT | Radio Frequency | Transmission Processing | Linux OS | Pytorch | Python | Causal Inference.
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Advanced data analytics designing and building solutions using technologies such as Azure Data Factory, Azure Data Lake, HD Insights, SQL DWH, Stream Analytics, Machine Learning, R Server, Synapse, Azure Machine Learning (AML), Azure Kubernetes Service (AKS) for model deployments, Vector and Retrieval-Augmented Generation (RAG) implementation.
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