TITLE: Senior Data Scientist (CB Information Services d.b.a. CB Insights New York, NY)
HOURS: 40 hours per week, Monday-Friday, 9:00-5:00
DUTIES: Analyze how data science projects impact the business & design solutions accordingly. Spearhead use of best practice in using various machine learning & NLP techniques & technologies. Identify root causes & develop solutions to improve robustness for the data science teams systems. Drive improvement of code quality & serve as an example to follow through code reviews. Deliver complex large-scoped features independently, including designing & implementing a solution that is running successfully in production. Develop data models to effectively gather information from disparate sources, analyze it, identify trends, extract useful information & surface the information onto our system platform. Develop end-to-end machine learning & NLP-based systems to extract structured information from unstructured data. Identify key areas for workflow improvements & develop tools to help reduce time for development of these systems. Share machine learning & NLP expertise via presentations & knowledge sharing sessions. Collect business intelligence data from available industry reports, public information, field reports, & purchased sources. Build standardized data products to extract business intelligence of companies & industries which supports data driven decisions. Document & disseminate information regarding tools & the developed systems. Utilize best practices for training, testing, & validation to build accurate & reliable models. EOE.
REQTS: Must have Masters degree or foreign equivalent in Computer Science, Quantitative Methods, Statistics, Economics, or a related quantitative field plus three (3) years of experience in the job offered, as a Data Scientist, or a related role. Must have three (3) years of experience with: using Machine Learning (ML) to design & implement data science solutions; analyzing business problems & the feasibility of a data science solution, data wrangling & visualization, & predictive modeling & fine tuning; developing Natural Language Processing (NLP) & Natural Language Generation (NLG) systems using industry best practices including information extraction, topic modeling, language modeling & linguistic surface realization; leveraging big data technologies & data warehouses including relational databases, Spark & Hadoop; statistical inference & modeling including hypothesis testing & model interpretations; experiment design & analysis; SQL; Python; version control systems & bash; defined & measured performance on machine learning systems for stakeholders; & documented deployed ML systems functionalities on the preservation of institutional knowledge.
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