World Wide Technology · 2 days ago

Data Scientist

Oakland, CA

Contract

Onsite

Mid Level

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Comp. & Benefits

Insider Connection @World Wide Technology

Discover valuable connections within the company who might provide insights and potential referrals, giving your job application an inside edge.

Responsibilities

Support Data-Science and other analytics as needed.

Develop SQL queries and data sets.

Develop business and client-facing reports.

Qualification

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Statistical Languages RStatistical Languages PythonStatistical Languages SQLData ArchitectureMachine Learning TechniquesAdvanced StatisticsProblem SolvingCommunicationCodingCC++JavaJavaScriptStatistical analysisData miningGLM RegressionRandom ForestBoostingText miningSocial network analysisDatabase queryingRPythonSQLWeb servicesRedshiftS3SparkMachine learning algorithmsRegression

Required

Strong problem solving skills with an emphasis on product development

Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets

Experience working with and creating data architectures

Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages drawbacks

Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications

Excellent written and verbal communication skills for coordinating across teams

A drive to learn and master new technologies and techniques

Experience manipulating data sets and building statistical models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field

Preferred

Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc.

Knowledge and experience in statistical and data mining techniques: GLM Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.

Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.

Experience using web services: Redshift, S3, Spark, , etc.

Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.

Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.

Experience with distributed data computing tools: Map Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.

Experience visualizing presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.