Sr. Data Scientist
Design, build, and optimize models for expanding our company-wide models not tied to specific customers, including text generation, text crosswalk with advanced Natural Language Processing (NLP), deep learning frameworks and architecture. Doing “full stack” machine learning, including backend, front end, infrastructure, also API implementation, deploy and serve machine learning models, and functions with software engineering team. Contribute research on up-to-date NLP and deep learning space. Reproduce novel architecture of deep learning models and algorithm in paper and create evaluating metrics based on statistical and mathematical theories. Utilize Python for backend data processing; design and develop internal libraries and tools used to automate and accelerate data model production. Build, modify, and maintain skills inference models for inferring employee skills from corporate data sources using Natural Language Processing (NLP) methods, machine learning, and data engineering techniques in AutoML. Load and transform massive-scale data payloads, including unstructured and textual data. Structure and solve problems, conducting and interpreting data analysis while demonstrating analytical and quantitative skills. Perform exploratory data analysis, generate and test working hypotheses, prepare and analyze historical data, and identify patterns in the data. Collaborate with a multi-disciplinary team of engineers and analysts on AI software projects. Telecommuting is permitted from any location in the United States.
Qualified candidates must have a Master’s degree in Computer Science, Data Analytics Engineering or related field, or foreign equivalent, and one year of experience with the following: Natural Language Processing (NLP); Machine Learning; Deep Learning; and Data Engineering. Telecommuting is permitted from any location in the United States.