Job Description:

• Perform advanced analytics tasks, including but not limited to predictive statistical models, customer profiling, segmentation analysis, data analysis and mining, and external data enhancement using SQL, SAS, R, Python or PySpark.
• Identify and test hypotheses, ensuring statistical significance, and builds predictive models and data visualization to support production business. Extract and process large quantities of data from data warehouses and other data marts in support of assignments.
• Analyze marketing metrics to identify cause-effect relationships between marketing levers and outcomes.
• Consolidate and package up insights, analytic outputs, and action items into a well-organized, consumable package with actionable recommendations and strategies for marketers (MS Excel, PowerPoint, Word, etc.)Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients and peers.
• Turn complex data into practical and actionable marketing insights.
• Support development of efficient and accurate project management plans for project delivery.

Qualifications:

• Bachelor's degree (or equivalent) required in any discipline with strong record of academic success in quantitative and analytic coursework such as Business Analytics, Data Science along with Computer Science.
• Expert in large distributed datasets using Hive SQL, Spark, Python. Solid knowledge of SQL in its various forms for traditional databases and distributed computing environments.
• Experience with Spark or Map Reduce, SQL and noSQL databases. Solid understanding of data mining and statistics concepts and familiarity with real-world applications of these techniques.
• Expert in commercial and/or open source statistics and data mining packages.
• Strong written and verbal communication, presentation, client service and technical writing skills for both technical and business audiences.
• Strong analytical, problem solving and critical thinking skills.
• Strong attention to detail, with a quality-focused mindset