ITmPowered, LLC
Data Analyst ML NLP Data Scientist Building the Future
Have you ever wanted to work on state-of-the-art natural language processing and applied machine learning that will make a real impact? We are looking for brilliant Machine Learning Data Analysts, Data Scientists, and Applied Statistics Analysts with strong experience in Python and R who have the passion to tackle tough problems by bringing cutting-edge ML technologies! As a Machine Learning Data Analyst and Data Scientist, you will do much more than just NLP solution development. You will develop algorithms, predictive models, and analytics to solve critical health service problems, reduce patient mortality, improve patient flow forecasting, and enhance the quality of care.
Responsibilities:
Partner with business executives and provide recommendations to leadership on appropriate application of analytics to business strategies and effectively communicate implications to senior leadership. Identify problems, develop recommendations, influence key stakeholders to adopt, and drive it to execution. Develop and apply algorithms and models to key business metrics to improve operations. Create data pipelines and data models using Python, R, SAS Text Miner, and KNIME. Use confidence intervals and significance of error measurements to develop and evaluate data sets. Design and develop data models, logical/physical database designs, big data pipelines, and ML algorithms. Leverage and expand your experience in NLP, ML, and AI algorithms and methods for information extraction, topic modeling, parsing, and relationship extraction. Use your knowledge of NLP concepts like TFIDF, N-gram Modeling, Stemming and Lemmatization, Entity Extraction, Sentiment Analysis, Document Classification, Topic Modeling, Natural Language Understanding (NLU), Natural Language Generation (NLG), and word embedding. Utilize text pre-processing and normalization techniques, such as tokenization, POS tagging, and parsing. Experience in producing, processing, evaluating, and utilizing training data. Provide data architectural leadership in developing enterprise data/process models and logical/physical database designs. Provide data and database development, maintenance, and support. Conduct research projects, incorporate project design, data collection and analysis, summarize findings, develop recommendations, and effectively communicate to leadership the impact on the business. Present findings, analysis, and recommendations to business executives for decision-making. Design distributed and scalable systems. Test and document the software you develop. Perform research, analysis, and modeling on organizational data. Build technical knowledge to support research and analytic responsibilities including neural networks, speech recognition, and natural language processing. Ensure that the delivered NLP Analytics products meet the business needs of the company. Requirements:
Bachelor's Degree in Applied Statistics, Math, Econometrics, or similar (or 4 additional years of experience). 4+ years as a Data Scientist and/or Sr. Data Analyst with strong use of Python and R. 3-6 years experience in text mining or NLP modeling and applications, using large amounts of text data, and extracting insights quickly using SAS Text Miner and KNIME. Knowledge of various machine learning techniques and key parameters that affect their performance. Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation of data sets, etc. NLP experience highly preferred; Knowledge of NLP concepts like TFIDF, N-gram Modeling, Stemming and Lemmatization, Entity Extraction, Sentiment Analysis, Document Classification, Topic Modeling, Natural Language Understanding (NLU), Natural Language Generation (NLG), and word embedding. Experience with NLP methods for information extraction, topic modeling, parsing, and relationship extraction. Understanding of text pre-processing and normalization techniques, such as tokenization, POS tagging, and parsing. Experience in Python, R, as well as SAS Text Miner and KNIME. Strong written and verbal presentation skills with an ability to communicate effectively with Senior Management by making complex concepts easy to understand. Logistics:
Local resources only. On-site only. No remote. NO sub- NO sponsorship available.
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Partner with business executives and provide recommendations to leadership on appropriate application of analytics to business strategies and effectively communicate implications to senior leadership. Identify problems, develop recommendations, influence key stakeholders to adopt, and drive it to execution. Develop and apply algorithms and models to key business metrics to improve operations. Create data pipelines and data models using Python, R, SAS Text Miner, and KNIME. Use confidence intervals and significance of error measurements to develop and evaluate data sets. Design and develop data models, logical/physical database designs, big data pipelines, and ML algorithms. Leverage and expand your experience in NLP, ML, and AI algorithms and methods for information extraction, topic modeling, parsing, and relationship extraction. Use your knowledge of NLP concepts like TFIDF, N-gram Modeling, Stemming and Lemmatization, Entity Extraction, Sentiment Analysis, Document Classification, Topic Modeling, Natural Language Understanding (NLU), Natural Language Generation (NLG), and word embedding. Utilize text pre-processing and normalization techniques, such as tokenization, POS tagging, and parsing. Experience in producing, processing, evaluating, and utilizing training data. Provide data architectural leadership in developing enterprise data/process models and logical/physical database designs. Provide data and database development, maintenance, and support. Conduct research projects, incorporate project design, data collection and analysis, summarize findings, develop recommendations, and effectively communicate to leadership the impact on the business. Present findings, analysis, and recommendations to business executives for decision-making. Design distributed and scalable systems. Test and document the software you develop. Perform research, analysis, and modeling on organizational data. Build technical knowledge to support research and analytic responsibilities including neural networks, speech recognition, and natural language processing. Ensure that the delivered NLP Analytics products meet the business needs of the company. Requirements:
Bachelor's Degree in Applied Statistics, Math, Econometrics, or similar (or 4 additional years of experience). 4+ years as a Data Scientist and/or Sr. Data Analyst with strong use of Python and R. 3-6 years experience in text mining or NLP modeling and applications, using large amounts of text data, and extracting insights quickly using SAS Text Miner and KNIME. Knowledge of various machine learning techniques and key parameters that affect their performance. Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation of data sets, etc. NLP experience highly preferred; Knowledge of NLP concepts like TFIDF, N-gram Modeling, Stemming and Lemmatization, Entity Extraction, Sentiment Analysis, Document Classification, Topic Modeling, Natural Language Understanding (NLU), Natural Language Generation (NLG), and word embedding. Experience with NLP methods for information extraction, topic modeling, parsing, and relationship extraction. Understanding of text pre-processing and normalization techniques, such as tokenization, POS tagging, and parsing. Experience in Python, R, as well as SAS Text Miner and KNIME. Strong written and verbal presentation skills with an ability to communicate effectively with Senior Management by making complex concepts easy to understand. Logistics:
Local resources only. On-site only. No remote. NO sub- NO sponsorship available.
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