data science developer

Job OverviewJob ID: J37258Specialized Area: Data ScienceJob Title: Location: princeton,NJDuration: 12 MonthsDomain Exposure: Healthcare, Insurance, Retail, Oil & Gas, IT/SoftwareWork Authorization: Client: To Be Discussed LaterEmployment Type: W-2 (Consultant must be on our company payroll. C2C is not allowed)Cleansing of large unstructured data and enabling analytical capability in order to query the data and address various business needs.Use unstructured and disjointed data sets for the purpose of independently generating actionable business insights as well as creating manageable analytical processes within the Data and Analytics groupBuild econometric and statistical models for various problems inclusive of projections, classification, clustering, pattern analysis, sampling, simulations, and so forthPredictive statistical models, segmentation analysis, customer profiling, analysis, survey design, and data mining.Research new ways for predicting and modeling end-user behavior as well as investigating data summarization and visualization techniques for conveying key applied analytics findingsPerform ad-hoc data mining and exploratory statistical tasks on very large data-sets related to the business s strategies.Prepare reports and presentations for senior data scientists and relevant stakeholders that will give insights for departmental as well as business wide decision makingExperiment with various technologies and tools with the vision of creating innovative data driven insights for the business at the quickest pace possibleTake initiative in evaluating and adapting new and improved data analytics approaches for the business, working with senior management for approvalTechnical Skills Required:Experience in data cleansing and preparation concepts and toolsProgramming Languages: Hands-on with at least 3 of the following: of Python, R, Perl, Java, ScalaStrong background in relational databases and SQLExperience working with statistical libraries and frameworks for predictive analyticsExperience with ML modeling tools and libraries (eg. TensorFlow)Knowledge or experience working with Jupyter or Zeppelin notebooksKnowledge of Hadoop will be a plus but is not requiredExperience and knowledge in the various types on neural net models (DNN, CNN)Expertise in probability and statistics, time-series analysis, or econometrics as well as experience in the use of machine learning methods, for example, linear regression, correlation, statistical significance, and so forth.Experience in data visualization concepts and toolsExperience in data warehousing and dimensional data modeling is an added plus but not requiredExperience in NLP techniques, concepts and libraries will be an added plus but is not required

#J-18808-Ljbffr