Sebastian Napiorkowski verfügbar

Sebastian Napiorkowski

Big Data Solutions Architect & Machine Learning Engineer

verfügbar
Profilbild von Sebastian Napiorkowski Big Data Solutions Architect & Machine Learning Engineer aus Stuttgart
  • 70173 Stuttgart Freelancer in
  • Abschluss: M. Sc. Computer Science, RWTH Aachen University
  • Stunden-/Tagessatz:
  • Sprachkenntnisse: deutsch (Muttersprache) | englisch (verhandlungssicher)
  • Letztes Update: 02.06.2020
SCHLAGWORTE
PROFILBILD
Profilbild von Sebastian Napiorkowski Big Data Solutions Architect & Machine Learning Engineer aus Stuttgart
DATEIANLAGEN
CV (05/2019)

Diese Anzeige ist nur für angemeldete Nutzer möglich.

SKILLS
Backend: Python, Django, Java, Jersey, Jetty, Java Script ES6, Node.js, Express, Android, Cloudera/Hortonworks Stack, Apache NiFi, Apache Kafka, Apache Spark
Databases: MySQL, PostgreSQL Apache HBase, Apache Hadoop, MangoDB, CouchDB, ElasticSearch, ELK-Stack, Cassandra, Memcached, Redis
Frontend: HTML 5, React, Java Script ES6, jQuery, d3.js, Android, Kibana, Tableau, Amazon Quicksight
Deployment: Docker, Amazon AWS ecosystem, EC2, S3, Google App Engine, Heroku, Apache, Linux Server
Data Science: numpy, sci-kit-learn, sci-py, pandas, machine learning, feature engineering, natural language processing, clustering
Miscellaneous: Git, Svn, Jira, Confluence, Slack, Google Analytics, IoT
PROJEKTHISTORIE
  • 07/2019 - 09/2020

    • DAX30 Konzern (Ludwigshafen am Rhein)
    • >10.000 Mitarbeiter
    • Sonstiges
  • Big Data Solution Architect & Information Retrieval Specialist
  • Conceptualization, architecture and development of a scalable Big-Data solution (as a R&D Datalake use case) for mass indexing file contents using bleeding edge natural language processing and machine learning algorithms on the Cloudera Hadoop Stack (HDP and HDF), Palantir Foundry and Kubernetes Deployment in Microsoft Azure.

    Technologies used
    • NiFi and MiNiFi for ETL
    • Apache Spark Processing (Java, Scala & Python)
    • Apache HBase
    • Elasticsearch Stack
    • Django Backend
    • React Frontend
    Features comprising i.a.
    • Raw text extraction from various file types
    • Language dependent indexing
    • Clustering Approaches (i.a. Latent Dirichlet Allocation, Latent Semantic Indexing, doc2vec)
    • Parse unstructured data into structured data
    • Named Entity Recognition (i.a. chemical entities) using Neural Networks
    • Entity Linking (Distant Knowledge)
    • Molecular Substructure Search

ZEITLICHE UND RÄUMLICHE VERFÜGBARKEIT
Stuttgart (150-200 km Entfernungsradius) oder mit hohem Remoteanteil
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