JOB DESCRIPTION
Work Schedule
Standard (Mon-Fri)Environmental Conditions
OfficeJob Description
COMPANY: Thermo Fisher Scientific Inc.
LOCATION: 5900 Martin Luther King Jr. Highway, Greenville, NC 27834
TITLE: Business Intelligence & Analytics Manager
HOURS: Monday to Friday, 8:00 am to 5:00 pm
DUTIES: Conduct full life cycle data infrastructure analysis from requirements gathering, business analysis, and design to implementation of advanced analytics initiatives, data integration/engineering, and business intelligence and data warehousing.
Interpret data and analyze results using data mining and statistical techniques from SAP ERP data to set up predictive analysis models and reports using Excel, SQL, and other data manipulation languages.
Establish close business relationships across the organization and partner with the business and IT teams to streamline existing and introduce enhanced reporting and analytical solutions focused on automation and improvement of finance processes by leveraging complex data sources derived from multiple internal systems.
Manage application and data integration platforms.
Collaborate with functional teams to provide analytics support for recurring business operating mechanisms, as well as ad hoc, time sensitive requests to advance key initiatives.
Help define standardized reporting and ensure data source integrity for high fidelity analytics.
Translate business intelligence into concise presentation formats to guide discussion and critical decision making for intended audience.
Travel: Up to 25% domestic and international travel required.
REQUIREMENTS: MINIMUM Education Requirement: Bachelor’s degree in Computer Science, Business Administration, Finance, or related field of study. MINIMUM Experience Requirement: 5 years of experience in business intelligence development and process transformation, or related experience. Required knowledge or experience with: Data Warehousing, Modelling and SQL to build and optimize queries and extract data; VBA and Python to handle large data sets and smoothen existing/redundant processes; Creating stand-alone dashboards using visualization tools (including QuickSight, Power BI & Tableau); Using business intelligence reporting / visualization tools (Excel, OBIEE, Business Objects, Cognos, Tableau, or Cubes); Data modeling and transformation of large scale data sources using SQL, Hadoop, Spark, Hive, EMR, or other Big Data technologies; and Scripting for automation (including Python, Perl, or R).
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