Aug 16, 2019

Lead Data Scientist

  • BravoTech
  • Arlington, TX, USA
Direct Hire

Job Description

Lead Data Scientist - Machine Learning

Lead role is more of a client-facing role - Consulting, coaching/mentoring, assisting/guiding the team and business. This is more of a leader. Keeping up what the market is doing. Client is open on the salary, so salary is not an issue. 

Lead Data Scientist –

  • 2-4 years hands-on experience with NoSQL data stores such as MongoDB, Cassandra, HBase, Riak or other technologies that embed NoSQL such as MarkLogic or Lily Enterprise required
  • 3-5 years data science experience or similar quantitative skills (statician, actuary) required
  • 5-7 years software engineering in languages to include Java, SAS, and Python required
  • 5-7 years hands-on experience with SQL databases and Business Intelligence tools such as Oracle, DB2, Postrges, MySQL, SAS, Cognos, Oracle BI Enterprise Edition, SAP Business Objects, or Tableau required

  • Evaluate, research, experiment with computational learning technologies in a lab to keep pace with industry innovation while assessing business impact and viability for use cases associated with efforts in hand
  • Work with statisticians, data engineers, application developers, and related groups to inform on and showcase capabilities of emerging technologies and to enable the adoption of these new technologies, computational learning, and associated algorithms
  • Work closely with statisticians, data engineers, application developers, other IT counterparts, and business partners to develop, integrate and deploy computational learning as part of applications
  • Code, test, deploy, monitor, document, and troubleshoot computational learning processing and associated automation
  • Educate and develop system engineers on distributed systems engineering so as to enable future data science and practice
  • Perform other duties as assigned
  • Conform with all corporate policies and procedures

  • Excellent knowledge of Linux, AIX, or other Unix flavors
  • Experience with recent computational learning technologies such TensorFlow, Caffe, Torch, Neon, SystemML, or Theano
  • Experience with directed analytic graph processing using Beam, Nifi, Flink, and/or Samza
  • Experience with messaging technologies such as Kafka, RabbitMQ, ZeroMQ, or MQTT
  • Experience with high dimensional visualization using t-SNE or PCA or other related technologies such as Ayasdi
  • Working knowledge of cloud based computational learning technologies such as Google Cloud Machine Learning, Microsoft Azure Machine Learning, or IBM Watson
  • Working knowledge of Rasa, Spacey/Prodigy, NLTK, Standford CoreNLP, ELMo, and other natural language understanding and processing frameworks and modeling

  • Demonstrated strong track record on delivering computational learning based solutions that solve complex analytical problems using quantitative approaches that are a blend of analytical, mathematical and technical skills
  • Excellent written and verbal communication skills
  • Experienced with solution development, deployment, and/or administration of distributed computational learning and/or analysis systems such as Spark, H2O, SAS Grid, Tensorflow, or Hadoop

  • Master’ s Degree or higher degree in operations research, applied statistics, data mining, machine learning, physics or related quantitative discipline required


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