Intern - Data Quality Automation

Key Skills

Algorithms, C# Programming, C++, Data structuring, Effective communication skills, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), Python Programming, PyTorch, R Programming, Scikit-learn, TensorFlow

Job Description

• • Develops and programs integrated software solutions, especially in support of the development, deployment and life cycle of machine learning models including MLOps.
  • Applies machine learning and statistical modeling techniques to business or research problems. Collects and analyzes data sources; develops, trains and evaluates models; creates visualizations of data properties and model performance. Deploys and maintains models
  • Works closely with business stakeholders and platform providers to gather requirements, understand business use case, review the current MLOPs practices/ modelling approaches and suggest improvements across engineering best practices, recommended tools and model building approaches
  • Work with business use cases for machine learning to instantiate engineering best practices and industry standards on platforms, to maximize business value and savings
  • Develops, modifies, and validates data classifiers using Machine Learning, Regular Expressions and Named Entity Recognition (NER) models
  • Experiences with Cloud based data environments, structured data environments such as relational data bases, semi-structured and unstructured data
  • Keeps knowledge and skills current by reading state of the art research papers and blog posts from industry and research labs. Studies new methods to understanding industry trends and emerging technologies.

  Education & Experience required

  • MUST be a university student enrolled in a Bachelor's Degree with 1 full year left to graduation (Bachelor's in Mathematics, Economics, Physics, Computer Science, or equivalent)
  • Experience with Machine Learning methods.
  • Experience with pattern matching and regular expressions and natural language processing methodologies (preferred).
  • Experience with recent ML Ops tools and solutions for development and deployment of ML solutions (preferred).
  • Familiarity with agile development processes.

  Knowledge & Skills

  • Fluent in one or more Machine Learning Frameworks (e.g. Pytorch, TensorFlow, scikit-learn, etc). Fluent in Python and knowledge of one or more additional programming Languages, such as C++, R, C#
  • Knowledge of modern computer science including algorithms, data structures, software architecture. Where applicable, knowledge of cloud and hybrid cloud service architectures and their impacts on development and deployment.
  • Experience with pattern matching and regular expressions
  • Knowledge of the Mathematics of Machine Learning (particularly Linear Algebra, differential calculus) and Statistics
  • Knowledge of data processing techniques and data preprocessing requirements for the common machine learning approaches. Knowledge of data collection techniques.
  • Knowledge of data augmentation approaches and their pros and cons.
  • Strong analytical and problem solving skills.
  • Good written and verbal communication skills in English and local language. 
  • Passionate about learning new technologies and sharing knowledge with the team.

  The Data Architecture and Governance team is seeking individuals with leadership and passion to accelerate development and adoption of effective Data Governance and Management standards working collaboratively with Business Groups, IT, Data and Analytics, Privacy and Legal teams to significantly improve data quality, enable efficient data management, data privacy and security compliance.
  This Machine Learning Engineer role will be responsible for developing and tuning machine learning algorithms to automate identification or personal data across HP systems, working in collaboration with Personal Data Discovery tool product manager and SW vendors.