Data Scientist

Responsibilities

As an NLP data scientist, you will:

• Research, design, implement, and deploy full-stack scalable computer vision, deep learning, and machine learning solutions to novel and R&D problems.
• ​The primary responsibility of this role will be designing and implementing NLP models and algorithms. Y
• ou enjoy creative and structured problem-solving. You like the challenge of working on complex challenges with structured and unstructured data and are capable of breaking a larger problem into sizable chunks to work on. T
• ranslate business requirements into quick prototypes or proof of concepts and work with customers directly to uncover operational objectives. D
• evelop and implement NLP solutions for text classification, sentiment analysis, and named entity recognitionC
• ollaborate with data engineers and cross-functional teams to deploy NLP models into production environments and optimize NLP solutionsA
• nalyze large datasets and provide insights to improve operationsP
• rocess, cleanse, and verify the integrity of data used for analysis and identify ways to improve data reliability, efficiency, and qualityC
• reate and maintain technical documentation for NLP models and algorithmsP
• articipate in code reviews and QA processesS
• elect features, build, and optimize classifiers using machine learning techniquesE
• nhance data collection procedures to include information relevant to building analytic systemsC
• reate automated anomaly detection systems Q

ualifications: B

achelor's degree in CS or related field.3+ years of experience in NLP or a related field.A PhD or MS in science, engineering, math, statistics, or related fields is a plus.Strong foundation and/or courses taken in programming (3+ yrs in Python, Java, Scala, R, or combined).    The ideal candidate should have experience developing NLP models with transformer architecture and expertise in transforming high volumes of data into advanced analytic solutions. Experience developing NLP models with transformer architectureExperience collecting, developing, and maintaining structured and unstructured data sets for analysis and reporting.Experience programming in Python or Java.Experience with machine learning frameworks such as PyTorch, TensorFlow, or KerasExperience with NLP libraries such as NLTK, Gensim, or SpacyExperience with cloud computing platforms such as Google Cloud or AWSExperience creating reports, projections, models, and presentationsKnowledge of cloud infrastructure, data modeling, ETL, data pipeline, log gathering, and visualizationExperience with Django, Flask frameworks is a plus.Excellent written and verbal communication skills and ability to communicate effectively to both technical and non-technical audiences.  Technical fluency; comfortable understanding and discussing architectural concepts and algorithms, assessing tradeoffs and new opportunities with technical team members.