23282-1 Remote Data Scientist/Client Engineer- 6 Months Contract ,100% Remote
Sigma Systems Inc is looking to hire a Remote Data Scientist/Client Engineer for their client.
Summary:
Machine Learning and Intelligent Assistance Team, builds, delivers and maintains the products, platforms and capabilities that enable Client's Business Units to leverage intelligent automation solutions to effectively engage/collaborate across teams internally and our customers externally. We build advanced AI technology solutions at a global scale that positively impact Client 's business performance.
We are looking for a Data Scientist/Client Engineer with NLP Focus to join the Intelligent Solutions Team to scale and help us improve our NLP products and create new efficient self-learning NLP applications and products.
Responsibilities
Understand business problems and objectives and develop strategy, roadmap to pilot and build NLP based software products that help to achieve business goals for business clients
Lead the development of scalable NLP and machine learning pipelines to deliver stable and efficient production-ready components and solutions
Develop and productionize real-world AI/Client applications such as prediction, recommendation, computer vision, NLP, sentiment, knowledge and content intelligence, etc.
Provide active hands-on guidance and leadership through the entire lifecycle of Machine learning development projects, including but not limited to: Classification, Document Summarization, Topic Modelling, Dialog Systems, Sentiment Analysis, OCR text processing
Requirements
Degree in Data Science, Computer Science, Informatics, life sciences, physics, applied mathematics, statistics or related field
5 years as a data scientist, Machine Learning or NLP engineer
5 years working with different types of enterprise and real world data sets – structured, semi-structured and unstructured data
3 years building Client/NLP based web or mobile applications
Strong understand of Software Engineering and Development Life Cycle principles
Good written and verbal communication skills
Experience in setting up supervised & unsupervised learning Client/NLP models including data cleaning, data analytics, feature creation, model selection & ensemble methods, performance metrics & visualization
Experience in text classification, feature extraction, named entity recognition, documentation summary
Hand on experience with machine learning techniques such as deep neural nets (DNN, CNN, LSTM-RNN)
At least 5 years' experience building Machine Learning & NLP solutions over open source platforms such as SciKit-Learn,Tensorflow, SparkML, Torch, Caffe, H2O
Excellent knowledge and demonstrable experience in using open source NLP packages such as NLTK, Word2Vec, SpaCy, Gensim, Standford CoreNLP.
At least 2 years' experience in designing and developing enterprise-scale NLP solutions in Agile context
Experience building production-ready NLP systems, from preprocessing and normalization to monitoring model drift in a production environment, ideally using NLP libraries and technologies including Spacy, PyTorch & Deep Learning models
Proficiency in leveraging cloud-based machine learning resources such as those from Amazon Web Services or Google Cloud for model training and productization
Experience with SoTA modeling techniques, such as transformers (e.g., BERT, GPT-_N_),
Experience in applying NLP in multi-lingual and multi-modal contexts
Experience taking an NLP project from concept to production
Experience in building, testing, and deploying computer vision based solutions
Collaborating via Git
Experience with hyperparameter optimization, model selection and validation
Experience with implementation of solutions with DevOps tools within the CI/CD pipeline (eg. Docker, Kubernetes)
Good proficiency with SQL, Python, Scala, or Java as well as formal statistical tools R, SAS, etc.
Experience in setting up supervised & unsupervised learning Client/NLP models including data cleaning, data analytics, feature creation, model selection & ensemble methods, performance metrics & visualization
Experience in text classification, feature extraction, named entity recognition, documentation summary
Hand on experience with machine learning techniques such as deep neural nets (DNN, CNN, LSTM-RNN)
At least 5 years' experience building Machine Learning & NLP solutions over open source platforms such as SciKit-Learn,Tensorflow, SparkML, Torch, Caffe, H2O
Excellent knowledge and demonstrable experience in using open source NLP packages such as NLTK, Word2Vec, SpaCy, Gensim, Standford CoreNLP.
Remote Data Scientist/Client Engineer
Sigma Systems Inc
2021-11-05T22:12:23Z
Collegeville
Pennsylvania
United States
Engineering
(No Timezone Provided)
23282-1 Remote Data Scientist/Client Engineer- 6 Months Contract ,100% Remote
Sigma Systems Inc is looking to hire a Remote Data Scientist/Client Engineer for their client.
Summary:
Machine Learning and Intelligent Assistance Team, builds, delivers and maintains the products, platforms and capabilities that enable Client's Business Units to leverage intelligent automation solutions to effectively engage/collaborate across teams internally and our customers externally. We build advanced AI technology solutions at a global scale that positively impact Client 's business performance.
We are looking for a Data Scientist/Client Engineer with NLP Focus to join the Intelligent Solutions Team to scale and help us improve our NLP products and create new efficient self-learning NLP applications and products.
Responsibilities
Understand business problems and objectives and develop strategy, roadmap to pilot and build NLP based software products that help to achieve business goals for business clients
Lead the development of scalable NLP and machine learning pipelines to deliver stable and efficient production-ready components and solutions
Develop and productionize real-world AI/Client applications such as prediction, recommendation, computer vision, NLP, sentiment, knowledge and content intelligence, etc.
Provide active hands-on guidance and leadership through the entire lifecycle of Machine learning development projects, including but not limited to: Classification, Document Summarization, Topic Modelling, Dialog Systems, Sentiment Analysis, OCR text processing
Requirements
Degree in Data Science, Computer Science, Informatics, life sciences, physics, applied mathematics, statistics or related field
5 years as a data scientist, Machine Learning or NLP engineer
5 years working with different types of enterprise and real world data sets – structured, semi-structured and unstructured data
3 years building Client/NLP based web or mobile applications
Strong understand of Software Engineering and Development Life Cycle principles
Good written and verbal communication skills
Experience in setting up supervised & unsupervised learning Client/NLP models including data cleaning, data analytics, feature creation, model selection & ensemble methods, performance metrics & visualization
Experience in text classification, feature extraction, named entity recognition, documentation summary
Hand on experience with machine learning techniques such as deep neural nets (DNN, CNN, LSTM-RNN)
At least 5 years' experience building Machine Learning & NLP solutions over open source platforms such as SciKit-Learn,Tensorflow, SparkML, Torch, Caffe, H2O
Excellent knowledge and demonstrable experience in using open source NLP packages such as NLTK, Word2Vec, SpaCy, Gensim, Standford CoreNLP.
At least 2 years' experience in designing and developing enterprise-scale NLP solutions in Agile context
Experience building production-ready NLP systems, from preprocessing and normalization to monitoring model drift in a production environment, ideally using NLP libraries and technologies including Spacy, PyTorch & Deep Learning models
Proficiency in leveraging cloud-based machine learning resources such as those from Amazon Web Services or Google Cloud for model training and productization
Experience with SoTA modeling techniques, such as transformers (e.g., BERT, GPT-_N_),
Experience in applying NLP in multi-lingual and multi-modal contexts
Experience taking an NLP project from concept to production
Experience in building, testing, and deploying computer vision based solutions
Collaborating via Git
Experience with hyperparameter optimization, model selection and validation
Experience with implementation of solutions with DevOps tools within the CI/CD pipeline (eg. Docker, Kubernetes)
Good proficiency with SQL, Python, Scala, or Java as well as formal statistical tools R, SAS, etc.
Experience in setting up supervised & unsupervised learning Client/NLP models including data cleaning, data analytics, feature creation, model selection & ensemble methods, performance metrics & visualization
Experience in text classification, feature extraction, named entity recognition, documentation summary
Hand on experience with machine learning techniques such as deep neural nets (DNN, CNN, LSTM-RNN)
At least 5 years' experience building Machine Learning & NLP solutions over open source platforms such as SciKit-Learn,Tensorflow, SparkML, Torch, Caffe, H2O
Excellent knowledge and demonstrable experience in using open source NLP packages such as NLTK, Word2Vec, SpaCy, Gensim, Standford CoreNLP.