• Application Deadline:
• Position: NLP Data Scientist


• Job Type Full Time


• Qualification BA/BSc/HND , MBA/MSc/MA


• Experience


• Location Abuja


• Job Field Data, Business Analysis and AI 
  

Responsibilities:

• Data Handling: Collect, preprocess, and manage large datasets. Perform data cleaning, annotation, and augmentation tsupport model training and evaluation.


• Performance Monitoring: Monitor and analyze model performance in real-world scenarios. Identify issues, troubleshoot problems, and implement improvements as needed.


• Collaboration: Work closely with other data engineers, machine learning engineers and domain experts tunderstand project requirements and deliver effective solutions. Communicate findings and results clearly tstakeholders.


• Research and Innovation: Stay current with the latest research and advancements in NLP and machine learning. Conduct experiments and explore new techniques tadvance our capabilities.

Qualifications

• Education: Bachelor’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field. A master’s degree or higher is preferred.

Technical Skills:

• Proficiency in Python and understanding in Pytorch is preferred.


• Strong understanding of NLP concepts and techniques, including tokenization, named entity recognition, and dependency parsing.


• Experience with NLP models and architectures such as Transformer, BERT, Tacotron2, Wave Glow, etc.


• Proficiency in data handling, data preprocessing, and data annotation, web scraping. (Required)


• Familiarity with evaluation metrics such as BLEU, ROUGE, WER, and MOS.

Experience:

• Proven experience in data handling, preprocessing and annotation of datasets.


• Demonstrated project experience in speech synthesis, speech recognition, or machine translation.

Soft Skills:

• Strong problem-solving skills and attention tdetail.


• Excellent communication and collaboration skills.


• Ability twork effectively in a team environment and adapt tnew technologies.

Preferred Qualifications:

• Experience with real-world applications of NLP and integration intproduction systems.