Lead process improvement, transformation, effective use of technology and data and analytics, and leveraging alternative delivery are key areas to drive value and continue to be recognized as the leading professional services firm.

More Uses of the Tensorflow Toolkit:

  • Lead: work closely with other experts and researchers on implementing algorithms that power customer oriented products.
  • Develop production grade Tensorflow models and work towards improvements in your existing customer facing machine learning systems.
  • Meet with non data science business stakeholders to set expectations and design products based on business needs.
  • Be accountable for developing image quality control architecture to ensure the quality and validity of training and real time images.
  • Keep your customers data and money secure by Identifying fraudsters and preventing fraudulent transactions.
  • Ensure you cooperate; lead research in advanced Artificial Intelligence, Machine Learning, and Deep Learning, majorly focusing on the long term research topics.
  • Drive: conduct applied research and development in natural language processing, deep learning, and machine learning.
  • Guide: by converting contracts, unstructured legal language, into structured data, you help clients understand risk and identify opportunities.
  • Standardize: research, prototype and develop innovative algorithms and solutions for real time object detection, instance segregation and object tracking.
  • Stay abreast of current industry and organization compiler research and communicate key ideas to others at Mythic.
  • Manage work with the larger data science team to analyze large data sets and develop custom models/algorithms to uncover trends, patterns and insights.
  • Be certain that your planning utilizes creativity and innovation to solve conceptual programming problems raised by cutting edge research.
  • Collaborate and knowledge share with internal stakeholders to ensure single source of truth for all data.
  • Ensure frequent communication with stakeholders to drive use case development and manage expectations of model limitations.
  • Coordinate: probabilistic models and bayesian models, machine/deep learning, reinforcement learning, and human in the loop online learning.
  • Arrange that your organization contributes to research designs, develops prototype implementations, and participates in the preparation of papers describing the research.
  • Provide data modeling, mining, pattern analysis, data visualization, and additional solutions to address business and customer needs.
  • Formulate: data science evangelist and an assessor in promoting new ways of diving into complex issues while assessing current practices and identifying areas where training or knowledge would help.
  • Analyze data sets, ranging from sparse datasets to large data and/or unstructured datasets, in order to extract insights, and drive further research opportunities.
  • Coordinate: successfully implement development processes, coding best practices, and code review for production environments.
  • Govern: conduct advance exploratory data analysis to discover statistically significant patterns and opportunities in your data.
  • Orchestrate: design and develop machine learning predictive models for various business problems using python and Tensorflow.
  • Manage work with expert engineering teams to deploy deep learning algorithms to a wide range of processing environments while maintaining your high standards for image quality.
  • Direct: design, develop, and integrate software systems and architectures necessary to realize research prototypes.
  • Ensure you carry out; build quick proof of concepts (poc) and project ownership around projects that can demonstrate utilization, value and lead to scalable solutions.
  • Lead: conduct applied research and development in multi modal AI applications that involve computer vision, natural language processing, speech processing, and other related techniques.
  • Collaborate with colleagues to develop analysis methods and algorithms to solve complex computational research problems.
  • Ensure you conduct; lead process improvement, transformation, effective use of innovative technology and data and analytics, and leveraging alternative delivery solutions are key areas of focus to drive additional value for your firm.

 

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