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Using natural language processing (NLP), machine learning (ML), Generative AI, and other relevant AI technologies and platforms; Analyzing Conversational (Chats, Emails, Messages and Calls) data, and the use of this data to build Natural Language (NLP) modeling pipelines for intent classification, training & deploying conversational AI systems, IVR, virtual assistants, chatbots etc.
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In this role specifical, the Principal Data Scientist (Deep Learning) will lead algorithmic solution design, rapid prototyping, and technical review for the ML/AI models underlying personalized user experiences and content promotion.
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2-5 years’ experience with Solid knowledge of FB/IG Ads/Business Manager & Google Ads, Google Analytics, TikTok and other ad platforms, including retargeting ad platforms. Google Ads and Facebook Blueprint certifications a plus.
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As a Staff ML Ops Engineer at SiriusXM, you will be a key player in our Data Platform Team. Your role will be pivotal in deploying, managing, and optimizing machine learning (ML) models, leveraging advanced tools like Databricks and MLFlow.
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Experience with parallel programming, machine learning, bioinformatics, cybersecurity, sparse linear algebra or graph databases is preferred. Experience with machine learning, bioinformatics, cybersecurity, sparse linear algebra, and/or graph databases are highly preferred.
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You have varied and hands-on predictive machine learning experience (deep learning, boosting algorithms, inference. 5+ years of working experience as Statistician, Data Analyst, Machine Learning Engineer, Data Scientist in digital marketing, advertising, healthcare, or other areas requiring customer level predictive analytics.
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Experience With Machine Learning Libraries and Frameworks (TensorFlow, MLlib, Pandas, Numpy) is an added advantage. Experience in the areas of design and implementation of Ratings Data Ingestion pipelines with modern AWS cloud and other technologies such as S3, Hive, Databricks, Scala, Python and Spark.
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Solid understanding of ML and AI foundations - Supervised/Unsupervised learning methods, deep learning architectures, Natural Language Processing (NLP), etc. Hands-on experience using modern big data pipelines (AWS, Google Cloud, Snowflake)AI/ML models, Natural language process (NLP) and data mining experience Required Experience:Degree within Computer Science, Data Engineering, or a related field.
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We are individuals who are data driven, and are passionate about making ML innovations in areas such as: Learning-To-Rank, Natural Language Processing, LLM, Reinforcement Learning to improve the Etsy search experience.
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Document classification and extraction: Data scientists can use natural language processing (NLP) techniques to classify and extract information from documents, such as news articles and social media posts.
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Hang draws from years of deep expertise in loyalty, game design, and finance with employees from leading companies like Google, Amazon, Apple, Meta, LinkedIn, Coinbase, Square, and Goldman Sachs.
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Advanced Data Analytics / Machine Learning Techniques / Large Language models. Design and build data processing pipelines using tools and frameworks in the Databricks/Azure ecosystem.
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You must be familiar with image processing, machine vision, and data engineering, and even better if you are interested in 3D rendering, deep learning, and computer graphics.
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Hands-on experience using modern big data pipelines (AWS, Google Cloud, Snowflake) AI/ML models, Natural language process (NLP) and data mining experience. Design and implement innovative machine learning algorithms that solve complex problems and provide actionable insights.
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Summary:We are seeking a motivated and skilled Data Scientist to join our team at DistroKid. The successful candidate will have a significant opportunity to design, develop and deploy Machine Learning models that empower our internal teams and make a real difference to our global community of artists.
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