SAS Analytical Consultant

SAS Analytical Consultant

SAS is seeking a full-time SAS Analytical consultant to work with our client, a Federal Government client in Chantilly, VA. We are seeking an experienced SAS Developer-Analyst to support a variety of development and analytical work. The consultant will need to be proficient and have experience with SAS Programming, SAS Studio and knowledge of Visual Analytics. The consultant must have excellent communication skills and must be able to communicate about the techniques developed and results of analysis both to executives and other analysts in the organization.

QUALIFICATIONS – ESSENTIAL

• Must be currently located in or willing to relocate to the Washington DC area.
• Must be willing to work from client site up to 5 days per week
• Bachelor's Degree in Business, Computer Science, Economics, Mathematics or related field.
• 2 years' of professional consulting experience involving implementations of analytical applications or data manipulation
• 2 years of analytics, business intelligence and/or data management experience.
• Prepare and manipulate structured and unstructured data for data discovery and mining from multiple disparate data sources
• Create new variables and perform ETL on structured data
• Translate data analysis into coherent reports and presentations for internal and external customers with varying degrees of technical knowledge
• Create high-end analytic visualizations, utilizing supervised and unsupervised learning using SAS software to support decision makers
• Prototype solutions using varied SAS software tools
• Assist with communicating key analytic findings to stakeholders
• Support and maintain production code and data as needed
• Ability to communicate with people of various technical and business backgrounds, including the ability to explain difficult technical concepts in simple terms to business users.
• Excellent written, verbal, and interpersonal communication skills.
• Ability to conceptualize clients' needs and translate into specific implementation strategies.
• Will be required to use SAS Tools to produce work and deliverables across the entire data analytics lifecycle from data management and prep to modeling and data visualization.
• Will attend in person meetings and establish relationships with client resources and seek to become a trusted advisor regarding end-user needs and SAS software use and products
• Develop an understanding of the client's data environment and how that applies to developing predictive models; that is, analyze and determine what data is available and necessary to create desired data mining model(s), to include reviewing available data sources and identifying appropriate variables (existing, or to be created) for the models.
• Develop SAS programs to access data from various sources (e.g., reading in data sources and producing datasets suitable for SAS analytics); this will most often include data preparation, analysis and predictive model development.
• Interpret statistical model results into business insights and presents findings to management.
• Ability to write SAS/SQL statements to store, retrieve, manipulate, integrate, validate, and summarize data.
• Be proficient in Base SAS programming (DATA step), SQL programming (i.e., use of SQL pass-through or PROC SQL), as well as the SAS Macro language for use in making code more efficient.
• Good written and spoken communications skills in English and thought-leadership skills.

MAJOR RESPONSIBILTIES/ACTIVITIES:

• Build a trusted relationship with the customer to provide practical and theoretical guidance in the business value of proposed solutions and set proper expectations to ensure customer satisfaction
• Strategize with sales team on objectives for customer meetings, understand how this activity relates to overall sales plan and provide functional solution leadership for sales opportunities
• Conduct discovery meetings to collect, analyze, clarify, and document business requirements during the sales cycle to support the implementation team and to produce a detailed solution proposal
• Provide reliable delivery of targeted project results through role as expert in the application of specific SAS methodologies, projects and technologies.
• Provide data and analytical expertise to projects.
• Understand client business pains and translating them into solutions.
• Collaborate with other professional services colleagues, project managers, and sales teams on customer implementations.
• Understand, utilize and communicate best practice methodologies and industry standards internally and externally.
• Participate in product and solution training to acquire and maintain a detailed level of product knowledge of core components of SAS offerings.
• Lead or assist with activities related to SAS analytics project discovery, definition, design, development, implementation and follow-on maintenance analytical environment.
• Prepare data mining data sets for modeling.
• Develop an understanding of the client's data environment and how that applies to developing predictive models; that is, analyze and determine what data is available and necessary to create desired data mining model(s), to include reviewing available data sources and identifying appropriate variables (existing, or to be created) for the models.
• Use SAS for data exploration, to include developing intuition about the data, the data structures, data types, data values, exploration of distributions, summary statistics and/or histograms.
• Develop SAS programs to access data from various sources (e.g., reading in data sources and producing datasets suitable for SAS analytics); this will most often include data preparation, analysis and predictive model development.
• Perform data and statistical analysis, predictive modeling, and data mining using a mix of third-party and internal customer data to identify customer insights and behavioral characteristics.
• Interpret statistical model results into business insights and presents findings to management.
• Provide on-going tracking and monitoring of performance of decision systems and statistical models.