Data Scientist

Employment Type

: Full-Time

Industry

: Information Technology



Sponsorship Not Available for this position No Third Party Firms Act as Data Scientist on team that works on all the critical dashboards and automation tool for pulling customer feedback from digital surveys, chat, and voice to be able to help digital teams address major pain points proactively to effectively and quickly address customers biggest pain points and help to reduce significant costs and call volumes in operations. Analyze and understand data sources APIs Design and Develop methods to connect collect data from different data sources. Design and Develop methods to filtercleanse the data Design and Develop SQL , Hive queries, APIs to extract data from the store. Work closely with data scientists to ensure the source data is aggregated and cleansed. Work with product managers to understand the business objectives. Work with cloud and data architects to define robust architecture in cloud setup pipelines and work flows. Work with DevOps to build automated data pipelines. bull Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. bull Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies. bull Assess the effectiveness and accuracy of new data sources and data gathering techniques. bull Develop custom data models and algorithms to apply to data sets. bull Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes. bull Develop company AB testing framework and test model quality. bull Coordinate with different functional teams to implement models and monitor outcomes. bull Develop processes and tools to monitor and analyze model performance and data accuracy. Brief Summary of Skills bull Data Scientist Adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action bull Strong experience using a variety of data miningdata analysis methods, using a variety of data tools, building and implementing models, usingcreating algorithms and creatingrunning simulations. bull Must have proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. bull Familiarity with HTTP and invoking web-APIs Exposure to machine learning engineering bull Exposure to NLP and text processing bull Experience with pipelines, job scheduling and workflow management bull Experienced in managing work with distributed teams bull Experience working in SCRUM methodology bull Proven sense of high accountability and self-drive to take on and see through big challenges bull Confident, takes ownership, willingness to get the job done bull Excellent written and verbal communications and cross group collaboration skills Competencies bull Strong problem solving skills with an emphasis on product development. bull Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets. bull Experience working with and creating data architectures. bull Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantagesdrawbacks. bull Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. bull A drive to learn and master new technologies and techniques. bull 5-7 years of experience manipulating data sets and building statistical models, bull Coding knowledge and experience with several languages C, C++, Java, JavaScript, etc. bull Knowledge and experience in statistical and data mining techniques GLMRegression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. bull Experience querying databases and using statistical computer languages R, Python, SLQ, etc. bull Experience using web services Redshift, S3, Spark, DigitalOcean, etc. bull Experience creating and using advanced machine learning algorithms and statistics regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. bull Experience analyzing data from 3rd party providers Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc. bull Experience with distributed datacomputing tools MapReduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc. bull Experience visualizingpresenting data for stakeholders using Periscope, Business Objects, D3, ggplot, etc.

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