Position: Data Trainer
Company: 1touch
Category: Data Science
Experience required: 2y
English level: pre

The Data Trainer is an integral part of the data management team, focusing on the collection, creation, and 
manipulation of  datasets for training and evaluation purposes. 
This role involves sourcing or creating relevant datasets, extracting comprehensive information about specific named entities,
building knowledge bases using various tools and techniques such as regular expressions, dictionaries, and checksum algorithms, and 
collecting and creating business documents that represent different types of business domains which contain relevant constraints of entities. 
This position requires a blend of advanced technical data skills and the ability to effectively communicate complex concepts.

Key Responsibilities:

Facilitate understanding of how to source and create large datasets and extract detailed information about specific named entities.
Develop comprehensive knowledge bases about different named entities using regular expressions, dictionaries, checksum algorithms, or other relevant methods.
Implement data training programs that emphasize the creation, manipulation, and understanding datasets.
Create and manage large datasets for machine learning training and evaluation.
Gather and formulate sets of business documents that depict various business domains, each encapsulating pertinent groupings of named entities.
Evaluate the effectiveness of training programs and implement improvements based on feedback.
Stay updated with the latest trends and advancements in data science, data management, and relevant technologies.
Foster a data-driven culture within the organization by demonstrating the power and potential of well-managed and understood data.


Qualifications:

Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field.
Proven experience in a data-focused role, such as a Data Trainer/Analyst or similar.
Experience in teaching or training, particularly with an emphasis on data collection, data creation, and knowledge base development.
Deep understanding of techniques for sourcing or creating large datasets, and extracting comprehensive information about specific named entities.
Proficiency in data management principles and tools such as regular expressions, dictionaries, and checksum algorithms.
Proficiency in data software and tools like SQL, Python and data visualization tools.
Exceptional communication skills, with the ability to explain complex data concepts in simple, understandable language.
Strong problem-solving skills and ability to think critically.
Ability to tailor training programs to different learning styles and levels of expertise.