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In this role, you will lead and contribute to new and ongoing research and development efforts that advance Epsilon's identity match abilities - leveraging data science, machine learning and other disciplines to create new data-driven capabilities for our real-time digital marketing business.
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Building data science, machine learning solutions using Python, Scala, Spark DataBricks, SQL or similar. probability, statistics, machine learning, anomalies/outliers’ detection, data correlation/feature analysis, machine learning models.
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Embark on a leadership role within the Blue Yonder Data Science and Machine Learning team as a Staff Data Scientist, steering our machine learning platform that processes real-time data and powers deep learning models, generating billions of predictions daily.
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Data science, machine learning, optimization models, Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms. Hands-on experience with data engineering (databricks, spark, dataflow, etc.
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Informatic, machine learning, malware, matlab, photonics, python, radar, robotics. Uses analytical rigor and statistical methods to analyze large amounts of data, extracting practical insights using sophisticated statistical techniques such as data analysis, data mining, optimization tools and machine learning techniques and statisticsLeads development and execution of statistical and mathematical solutions to business problems to support larger initiatives.
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Reporting to the Senior Manager of Applied Machine Learning, the Principal Applied Machine Learning Scientist will build scalable machine learning applications by developing and deploying machine learning and deep learning models that improve the effectiveness of our business operations, designing machine learning processes against requirements and automating work across the organization to improve our speed and efficiency.
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Distributed processing, warehousing, and orchestration frameworks (e.g., Spark, Hive, Airflow) Experience in recommendation systems, search and learning to rank techniquesAt SiriusXM, we carefully consider a wide range of factors when determining compensation, including your background and experience.
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What you’ll do:Research, design, experiment with, and build machine learning systems for processing image and video content to improve the quality of search and recommendation experiences across SiriusXM and Pandora products.
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3+ years of Experience with Machine Learning platforms (AWS Sagemaker, Databricks), Data Pipelines (Spark, Airflow), CI/CD, GitHub, and visualization (Power BI/Tableau). Proficient in analyzing and modeling big data utilizing statistical, machine learning, and deep learning techniques.
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Involved in extensive research and problem solving that spans a number of areas including computer vision, machine learning, image processing and distributed computing. Research and development of computer vision and machine learning algorithms for object detection, recognition, segmentation, and tracking.
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5 or more years of experience executing data science projects involving advanced techniques (such as NLP, Generative AI, statistical analysis, predictive modeling, financial forecasting, data visualization, and machine learning) from beginning to end.
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Required to have Bachelors/Masters/Ph. D. in Statistics/Machine Learning/Data Science/Analytics /Computer Science or Engineering from premier institutes. Demonstrated strong capability in statistical/Mathematical modelling or Machine Learning or Artificial IntelligenceDemonstrated skills in programming for implementation and deployment of algorithms preferably in Statistical/Client based programming languages in Python.
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Experience in one area of computer science (e.g., Natural Language Understanding, Computer Vision, Machine Learning, Deep Learning, Algorithmic Foundations of Optimization), with publications in NeurIPS, ICML, ICLR, AAAI, KDD, CVPR, EMNLP, ACL.Experience with one or more general purpose programming languages (e.g., Python, Java, C/C.
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Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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