Sr Data Scientist - Machine Learning at GM Financial in Arlington, TX

Overview

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.​

Responsibilities

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

Qualifications

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

Ability to accept change and to adapt to shifting organizational challenges and priorities

Ability to coach, develop and lead others

Ability to evaluate problems and issues quickly, and to make recommendations for courses of action

Ability to make independent decisions and use sound judgment in relation to the management of team members

Ability to prioritize tasks and ensure their completion in a timely manner

Advanced ability to analyze problems, correlate data from multiple sources and communicate pertinent information to the appropriate support teams

Excellent analytical and troubleshooting skills

Strong interpersonal, verbal and written skills

EDUCATION

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

EXPERIENCE

2-3 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

2-3 years data science experience required

3-5 years ​​​software engineering in languages to include Java, SAS, and Python required

3-5 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