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Certificate in business analytics, data mining, or statistical analysis, Statistical programming languages (for example, SAS, R) Languages: R, Python (Pandas, Seaborn, Scikit-learn), SQL,Hive, Pig, Impala, Sqoop, Kafka, VBA, Shell.
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Well-versed in core advanced analytics data mining & scripting tools such as Python, R, and SQL. Performing statistical analysis & scripting using Python or R; developing dashboards in Tableau.
$75,000 - $90,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Conceive and coach the design of end to end scripted analytics solutions using Python, Scala, Java, or R as well as modern analytical systems in Spark + Hadoop/Databricks/Snowflake. PREFERRED QUALIFICATIONSAdvanced degree in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field.
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Proficiency in common database/programming/scripting languages (e.g., SQL, R, Python, Perl, Java, MATLAB, C. Proven computational experience with solid knowledge of informatics tools and visualization/data mining package.
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Basic coding knowledge and experience in several languages for example: R, Python/ Jupyter, SAS, Java, Scala, C. Basic to substantial experience in one or more of the following commercial/open-source data discovery/analysis platforms: RStudio, Spark, KNIME, RapidMiner, Alteryx, Dataiku, H2O, SAS Enterprise Miner (SAS EM) and/or SAS Visual Data Mining and Machine Learning, Microsoft AzureML, IBM Watson Studio or SPSS Modeler, Amazon SageMaker, Google Cloud ML, SAP Predictive Analytics.
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Strong programming skills in at least one language such as Python, R, C. Experience with machine learning, data mining, and statistical modeling. Working with the firm's trading, operations, finance, sales, banking and investing businesses, engineers use their mathematical and scientific training to create financial products, advise clients on transactions, identify market opportunities, assist managing risks, and provide technical solutions to facilitate all business activities.
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Experience using statistical computer languages (R, Python, SQL, etc.) Experience querying databases and using statistical computer languages: R, Python, SLQ, etc. Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
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The qualifications you need: 2-3 years working experience in IT-Consulting, Management Consulting, Process Improvement or a similar areaProficiency with SQL or other programming languages (Python, R, Matlab.
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Experience programming in three or more of the following languages—Matlab, R, Python, JAVA, SQL, OpenGL, C. Persons with a strong background and interest in statistics, machine learning and data mining are encouraged to apply.
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Fluency in MS Excel and common programming / query languages such as SQL, Python, R. Proficiency in principles and methods of data management, i.e., ETL, data validation, data mining.
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Must possess strong knowledge and real life experience in working with SQL (Hive) and Object Oriented Programming tools (Python, R) Lead automation of risk reporting in the enterprise analytics platform utilizing Hive, Python and R.
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You have practical experience in one or more of the following programming languages: Scala, Python, Java, or R. · Leverage your broad familiarity with basic concepts in probability and statistics, along with exposure to basic foundations of computer science, graph mining, and machine learning.
$123,900 - $227,200 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Special Licensing or certifications: Experience required in any of the following market leading data & analytic tools but not limited to: SAS, Snowflake, Python, R, Alation, Informatica or similar.
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Proficiency in statistical computer languages (e.g., R, Python) for data manipulation and analysis. Experience querying databases and using statistical computer languages (e.g., R, Python.
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Experience across broad range of modern data science and analytics tools (e.g., SQL, Hive, Hadoop, Spark, Python, R). Knowledge of modern data mining, quantitative research, and data science techniques (e.g., machine learning, behavioral analytics.
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