Job Description :
Title: Data Scientist Duration: 6 months Location: Stamford-Connecticut Job Description Discover insights hidden in multiple BI data warehouses Directly contribute to all phases of the analytics life-cycle with hands-on execution Survey varied data sources in relational databases, Hadoop, flat files, and external sources for analytic relevance Execute the full-scope of advanced analytic techniques Perform problem formulation, requirements analysis, and planning Responsible for data surveying, profiling, and pre-processing Synthesize appropriate recommendations for action and changes Help explain techniques and tools used to a broad set of business-intelligence, data, and analytics professionals with varied backgrounds Perform other duties as required. Advanced ability to combine, summarize, and interpret data. Advanced logical and analytic skills Advanced skills and experience with SQL (required) and R (desired) (including relevant packages) in support of advanced analytics Advanced-level skills with relational databases, including SQL and utilizing data stored in complex schemas Experience with the modelling process using a variety of algorithms Interpretation of model results, consideration of causality Strong synthesis and presentation skills Ability to communicate results and recommendations to a wide variety of audiences Basic understanding of data architecture, data warehouse and data marts Experience in the telecommunications industry, or two other consumer-based industries Demonstrated ability and desire to continually expand skill set, and learn from and teach others. Experience with Teradata: SQL, UDFs, interpreting explain plans, basic performance-tuning, and use of database catalog Operations-research background, in particular focused on large labor operations such as field ops, technical support, and sales Background with Cable systems and operations Experience with Hadoop, particularly HIVE and Spark Experience with other relevant tools such as Python, SAS, SPSS, Alteryx, Linux Experience with other relevant techniques such as text analysis and text mining Familiarity with the open-source ecosystems surrounding R (CRAN), Python (PyPi), and/or Hadoop