• Financial Services Pre-Sales Solutions Architect

    Job Locations US-NC-Cary | US-NY-New York City | US-CA-San Francisco
    Requisition ID
    Visa Sponsorship
    Travel Requirements
  • Overview

    Germany SAS


    We are seeking a focused Data Scientist, Pre-Sales Solutions Architect on the Financial Services Data Science team. You will provide both business and technical skills assisting the Pre-Sales team to ensure the highest levels of customer satisfaction and maximize revenue opportunities. This role is focused primarily on analytical sales support and enablement. Your activities will include, but are not limited to demoing AI applications, developing/delivering analytics workshops, assisting with Proof-Of-Concepts (POCs), and delivery presentations to a wide range of audiences. Having the ability to relate technical concepts and business requirements to SAS and clients is essential. Excellent public speaking skills both in small and large group settings are also required. You should have the capability to represent the entire SAS technology suite of products/solutions. The Financial Services Data Science team helps clients understand how SAS data, discovery and deployment provide the insights to make better decisions.


    • Understand detailed customer requirements and how SAS can competitively achieve them.
    • Become proficient with the use of SAS Analytics software portfolio. 
    • Build a trusted relationship with team members, other Pre-Sales members, Account Executives and clients as part of providing practical and theoretical guidance in the business value of the proposed solution and set proper expectations to ensure customer satisfaction.
    • Strategizes with sales team on objectives for customer meetings, understanding how this activity relates to overall sales plan and provides functional solution leadership for sales opportunities.
    • Assist with scoping, supporting and delivering customized client POCs.
    • Assist in defining best practices for delivery and implementation of SAS solutions for IT.
    • Identify enterprise-wide view of gaps and identify opportunities to leverage software technologies to eliminate those gaps.
    • Communicate SAS’ functional and technical differentiators. 
    • Present to executive level audiences the SAS technology.


    • Master's degree in a Quantitative Field (Physics, Math, Statistics, Operations Research, Engineering, Computer Science, etc) with extensive knowledge in the application of statistics.
    • 4+ years’ experience applying relevant machine learning and data modelling techniques used in supervised problems such as decision trees, Random Forests, Gradient boosted machines, linear/logistic regression, deep learning or unsupervised problems such as clustering and dimensionality reduction in at least one statistical tool/language (SAS, R, Python, etc.). 
    • Ability to interpret business requirements, translate into data science problems and deliver high value outputs.
    • Experience with credit underwriting, fraud or marketing application in Financial Services industry.
    • Ability to communicate with people with various technical backgrounds, think analytically, write and edit technical material, and relate statistical concepts and applications to statistical and non-statistical SAS users.
    • Ability to travel 30-50% of the time or as business requirements dictate at management discretion.
    • Locations: Cary, NC, New York City and San Francisco.

    Preferred Skills:

    • Programming script skills – e.g. shell, Python, and SAS.
    • Strong knowledge of applied statistics, probability, data modeling techniques, predictive modeling techniques.
    • Experience with Deep Learning, Artificial Intelligence, Analytics for Event Stream Processing, or Decision Management software.
    • Experience with R, TensorFlow, MXNet, Caffe2, Microsoft Cognitive Toolkit and their libraries.
    • Strong customer presentation, demonstration, public speaking, and interaction skills 
    • Ability to communicate with people of various technical backgrounds, think analytically, write and edit technical material, and relate statistical concepts and applications to statistical and non-statistical SAS users.
    • Strong problem solving, organizational, decision-making skills. 
    • Clear understanding of sales strategies and cycles. 
    • Ability to work effectively within a team and work independently.
    • Experience working across industries including but not limited to retail, financial services, communications, high tech, manufacturing and healthcare.
    • Experience in IoT, public and private cloud environments.


    • Equivalent combination of education, training, and relevant experience may be considered in place of the requirements above.



    SAS looks not only for the right skills, but also for a cultural fit. We seek colleagues who will contribute to the unique culture that makes SAS such a great place to work. We look for the total candidate: technical skills, culture fit, relationship skills, problem solvers, good communicators and, of course, innovators. Candidates must be ready to make an impact.


    Additional Information:

    • To qualify, applicants must be legally authorized to work in the United States, and should not require, now or in the future, sponsorship for employment visa status.
    • SAS is an equal opportunity employer.  All qualified  applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status or any other characteristic protected by law.
    • The level of this position will be determined based on the applicant's education, skills and experience. Resumes may be considered in the order they are received. SAS employees performing certain job functions may require access to technology or software subject to export or import regulations.
    • To comply with these regulations, SAS may obtain nationality or citizenship information from applicants for employment.
    • SAS collects this information solely for trade law compliance purposes and does not use it to discriminate unfairly in the hiring process.


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