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Experience with search architecture tools (ex - Solr, ElasticSearch) Data Science frameworks such as Keras, Tensorflow, or Theano. Our work depends on Software Engineer Senior joining our team to develop algorithms, write scripts, build predictive analytics, use automation, apply machine learning and use the right combination of tools and frameworks to turn a set of data points into objective answers to help senior leadership make informed decisions.
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Integrate the Solr search platform with AEM Adobe Sites, including implementing advanced search features such as multi-language support, geographic location data, signal ranking, and natural language processing.
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Deep familiarity with one or more of the following areas at scale: Lucene-based search systems (ElasticSearch or Solr), search ranking and retrieval, data science, or information taxonomy.
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Hands on experience architecting and delivering solutions using the Azure Data Analytics platform and solutions including but not limited to Azure Databricks, Azure Cosmos DB, Azure Data Factory, Azure Logic Apps, Azure Functions, Azure Storage, Azure SQL Data Warehouse, Azure Data Lake, Azure Search, and Snowflake.
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Involvement in the analyses of unstructured and semi-structured data, including latent semantic indexing (LSI), entity identification and tagging, complex event processing (CEP), natural language processing (NLP), and the application of analysis algorithms on distributed, clustered, and cloud-based high-performance infrastructures.
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Search tools: Solr , Lucene, Elasticsearch. Data science tools/languages: R, R Studio, Python (data preparation and analysis libraries), Databricks, etc. This role spans the spectrum of data capabilities from data vision and strategy all the way through data science, in addition to cloud, DevSecOps , and integration capabilities.
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Serve in role such as database developer/administrator, ETL developer, data analyst, BI analytics developer, and/or solution developer of contextual search applications. Utilize experience with tools including Cloudera CDH, CDP, Amazon Web Services, EMR ecosystem (such as SOLR, Spark, Impala, Hive, Hue, Athena, Glue, etc.
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Experience with major search vendors (e.g., ElasticSearch, Google, Solr / Lucene). Experience with the design, implementation, and maintenance of data pipelines including data storage, ingestion, transformation, and orchestration using scripting language (e.g. Python) or tool based (e.g. Databricks) solutions.
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Test Data management, SQL, API, Data Mining, Data Analysis, ETL, Cloud, Elastic Search. Experience in 2 or more Databases listed- Oracle, Couch, SOLR, MongoDB, Cassandra, etc.
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Search engine concepts like Apache SOLR, Elastic search. We offer challenging opportunities in front-end and back-end web application development, UX design, project management, business analysis, business intelligence, big data, and more.
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Working experience with Spark, Sqoop, Kafka, MapReduce, NoSQL Database like HBase, SOLR, CDP or HDP, Cloudera or Hortonworks, Elastic Search, Kibana, etc. and experience with data formats like json, csv, xml.
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Experience in Big Data, search, NLP, and chatbot technologies such as Elasticsearch and Solr. The AI COE is seeking a Senior Data Scientist with experience in Conversational AI, Generative Large Language Models, Natural Language Processing, Machine learning, various deep learning related technologies, predictive and prescriptive analytics.
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Extensive hands-on experience with NoSQL (e.g. Mongo, Cassandra), Kafka, search engines (e.g. Solr, Elastic), cache (e.g. Redis, Memcached), and other data sources. Ability to do production issues debugging using logs (e.g. Splunk), monitoring metrics (e.g. Prometheus), data sources, and knowledge of the application business logic.
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Experience with Search and Merchandising (Solr, Elasticsearch, or similar). Experience with Product Information Management / Master Data Management (Stibo STEP, or similar). Experience with defining, utilizing, and guiding the appropriate use of various data integration techniques (ETL, EAI, EII), including understanding the components within, capabilities of, and appropriate "fit to purpose" of Service Bus and Microservices Architectures.
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You've used several data storage technologies like Elasticsearch, Solr, PostgreSQL, MongoDB, or Cassandra and have some idea how they work and why they work that way. This is a senior software engineering role that focuses on enhancing the vector similarity search functionality within Elasticsearch, covering the design and implementation of new vector search features, enhancements to existing vector search functionality, and resolving bugs.
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