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Understanding of database design concepts (Pluggable DB's) and data modeling for relational or nonrelational databases such as RDBMS (Oracle/Postgres), No SQL (MongoDB, Cassandra) or NewSql (Cockroach DB) and search DB's like Elasticsearch incorporating multi-master across multi-regions.
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Demonstrated experience with search architecture and data visualization tools (ex - ElasticSearch, OmniSci) · Familiar with Data Science frameworks such as Keras, Tensorflow, or Theano.
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Specific Skillset We're looking to augment our existing team with someone who has deep experience in managing a large Elasticsearch cluster indexing machine learning vectors that power many features in our product including dataset search.
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Proficient in Elastic to support Data Management, Searching Data, Develop Search Applications, Data Processing and Cluster Management. The objective of this task order (TO) is to provide technical and program support services for the installation, maintenance, support, operations, and continuity transition process of an Elastic Search, Logstash, and Kibana (ELK) cloud-based solution for the DOT Enterprise Logging System.
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Joining our team as a Data Scientist specializing in Elasticsearch optimization offers a unique opportunity to work with leading-edge technologies and collaborate with clients to drive tangible improvements in search performance and accuracy.
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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.
$127,000 - $165,000 a yearExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Our data science stack includes AWS EMR, Apache Spark (core, mllib, and streaming), Elasticsearch and raw Lucene, scikit-learn, and more. The data team is developing groundbreaking technology for legal document recommendation and search.
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Incorporate user signals, machine learning and other data or tools to build a search service that continuously learns and improves. Experience with Elasticsearch, Machine Learning and NLP.
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Create and manage Elasticsearch Clusters on premise, including configuration parameters, indexing, search, and query performance tuning, RBAC security governance, and administration. Data ingestion & enrichment from various sources, webhooks, and REST APIs with JSON/YAML/XML payloads & testing POSTMAN, etc.
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You have experience in backend engineering, data infrastructure, search infrastructure or natural language processing/machine learning. You’ll improve search latency and relevancy using large scale data systems and machine learning.
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Experience in information retrieval or semantic search using vector databases or Elasticsearch. You’ll architect offline and online data pipelines to performantly extract, transform and load data to power Moonhub’s core search application.
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Experience with search architecture tools (ex - Solr, ElasticSearch) Torin is looking for a qualified Data Scientist 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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You have strong experience with data storages, such as relational databases (PostgreSQL) and search engines (ElasticSearch); you have experience with Big Data technologies (Apache Spark, Apache Kafka.
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Experience in integrating application with indexed search services such as Elasticsearch, Solr. Extensive Data Engineering experience in building low-latency, high throughput Data Pipelines that power Data Lake and Data Warehouse Solutions.
$153,550 - $230,350 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Hands on Scripting & Programming in Python, Ansible, bash, data parsing (regex) etc. Design and configuration of ETL data pipelines using Elastic Common Schema to onboard application logs and metrics; Configuration of index templates and data life cycle management ILM for data retention.
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