Job description

Job Summary:

Build and improve machine learning and analytics models. Work with other data scientists, SMEs, and Technical resources to create, optimize and productionize of machine learning models for various business units within the organization. Keep innovating and optimizing data and machine learning workflow to enable data-driven business activities at large scale.

Essential Duties and Responsibilities:

  • Provide industry insight; technical and analytical support using machine learning, deep learning, pattern matching, data visualization, and predictive modeling tools to produce analysis and algorithms that help businesses make better decisions.
  • Build advanced analytics applications from data (structured and unstructured) on various technology platforms (cloud and big data platforms)
  • Execute analytics with the right balance of business and technical skills
  • Makes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices
  • Proposes and builds innovative and effective data science solutions and strategies to address topmost business challenges
  • Leads discovery processes with business stakeholders to identify the business requirements and the expected outcome
  • Able to integrate data from Automation/Inspection/Packaging/Robotic machines and enable data collection from IoT devices on legacy machines and processes for Machine Learning and AI solutions
  • Collect, analyze and interpret qualitative & quantitative data with statistical theories and methods
  • Apply standard process CRISP-DM (business understanding, data understanding, data preparation, modeling, evaluation, deployment), Machine Learning frameworks such as TensorFlow, PyTorch etc. & Agile Methodologies for Business Analytics projects
  • Create and review technical design documentation, researches, including proposals, white papers, presentations, formal recommendations and reports
  • Provides guidance to junior data scientists
  • Contributes to the company by creating patents and other intellectual property
  • Update job knowledge by studying state-of-the-art development tools, programming techniques, and computing equipment; participating in educational opportunities; reading professional publications; maintaining personal networks; and participating in professional organizations
  • Protect operations by keeping information confidential
  • Collaborate with other ML and AI team members to define requirements, develop, and test solutions

Knowledge, Skills and Abilities:

  • Strong understanding, conceptualizing and hands-on working knowledge using Data Science and Statistical methods for AI/ML including Deep learning methods (Convolutional Neural Networks, Recurrent Neural Networks and Generative Adversarial Networks)
  • Extensive experience in software development cycles and excellent programming skill with scripting languages & frameworks eg. Python, R, Scala, Java, TensorFlow, PyTorch, Sklearn.
  • Familiar with micro service and/or big data technologies, eg. Openshift, Cloudera(CDH), Elasticsearch, CEPH.
  • Good understanding of cloud-based AI/ML products from Google, Azure, and AWS.
  • Good knowledge of Agile Methodologies
  • Experience in best practice adaption and external benchmarking
  • Must have the ability to work under deadline pressures and meet project objectives within a reasonable schedule
  • Passion about machine learning and data-driven intelligence system
  • Excellent communication and presentation skills in English
  • Team player, self-starter, ability to work on multiple projects in parallel is necessary
  • Strong work ethic. Fast learner with energy and enthusiasm
  • Perform other duties as assigned

Educational/Certification Requirement:

  • PhD/Masters/Bachelors in Computer Science, Computer Engineering, Statistics, Applied Mathematics, or related disciplines

Experience Requirement:

  • Work Experience: Minimum 5-8 Years’ experience in the related field
  • Experience in leading multi division projects

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