Lead Data Scientist-Machine Learning

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GM Financial
Machine Learning, Spark, H2O, SAS, Python, R, RStudio, Natural Language Processing, Deep Learning
Full Time
Work from home not available Travel not required

Job Description



We are expanding our efforts into complementary data technologies for decision support in areas that capitalize on intelligent applications enabled with computational learning. Our interests are in enabling intelligent applications and corresponding computation learning processing on large and low latent data sets with elastic cloud architecture techniques on premise.To that end, this role will engage with team counterparts in exploring and deploying technologies for engineering features and creating algorithms that result in models incorporated into intelligent applications. Application use cases are expected to focus on core aspects of our business such as risk management and customer experience. Responsibility also includes coding, testing, and documentation of new or modified scalable analytic data systems including automation for deployment and monitoring. This role participates along with team counterparts to architect an end-to-end framework developed on a group of core data technologies. Other aspects of the role include developing standards and processes for computational learning projects and initiatives.



JOB DUTIES



  • 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 company policies and procedures



Knowledge



  • 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


Skills



  • 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


Education



  • High School Diploma or equivalent required

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


Experience



  • 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 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 BusinessObjects, or Tableau required


Working Conditions



  • Normal office environment subject to stressful situations

  • Flexible schedule with possibility of working long hours including weekends/holidays, occasional overtime may be required

  • Limited travel may be required to support business needs

Posted By

GM Financial



Company Information

GM Financial, a wholly owned subsidiary of General Motors, is a global provider of auto finance solutions, with operations in the U.S., Canada, China, and Latin America. We employ more than 9,000 hard-working team members in North America, and we're always looking for new people with diverse talents. GM Financial is a workplace where dedicated people have the opportunity to work together and celebrate our successes. Our culture is based on respect, integrity, innovation and personal development.
Dice Id : 10120555
Position Id : 202036953-203
Originally Posted : 2 weeks ago

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