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ASRC Federal

Junior Logistician, SAS

Posted Yesterday
Be an Early Applicant
In-Office or Remote
Hiring Remotely in NC, USA
Junior
In-Office or Remote
Hiring Remotely in NC, USA
Junior
Supports the US Coast Guard Aviation Logistics Center by analyzing product life cycles, provisioning, allocation, demand forecasting, supply planning, and disposal. Develops supply optimization models, recurring reports, visualizations, business case analyses, and sensitivity analyses to improve aircraft fleet readiness and asset availability. Builds expertise in logistics modeling, forecasting methodologies, planning software, and statistical analysis tools while learning project timeline and communication practices.
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ASRC Federal is a leading government contractor furthering missions in space, public health and defense. As an Alaska Native owned corporation, our work helps secure an enduring future for our shareholders. Join our team and discover why we are a top veteran employer and Certified Great Place to Work™

Agile Decision Sciences (ADS), a wholly owned subsidiary of  ASRC Federal is seeking a Junior Logistician with an aptitude for Data Analytics (SAS, Power BI, Tableau, Python or R) to join our team supporting the US Coast Guard's Aviation Logistics Center.  Logistics and data analysis are the key to keeping the USCG's aircraft fleet operational and ready for the challenge.  If you want to grow your skills in planning, modeling, forecasting and applying supply chain concepts, join a mission that keeps our country safe, apply today.   

Requirements:

  • BA/BS in one of the following:  Supply Chain, Logistics, Industrial Engineering, Business, Engineering, or Information Systems Management OR
  • BA/BS degree in any field with 2 years of current logistics experience OR 4 years of logistics experience and an Associate's degree or HS Diploma.
  • Internship or classroom training with the life cycle of a product (aircraft product desired)
  • Experience or classroom training with provisioning, internal allocation, distribution and delivery.
  • Experience or classroom training with statistical analysis or modeling.
  • Experience with statistical analysis tools or programming languages such as SAS strongly preferred; SPSS, Python or R is a plus.
  • Any experience in formulating, planning and executing supply optimization using mathematical models is a plus.
  • US Citizenship is required for the clearance.

Responsibilities:

  • Evaluating the entire life cycle of a product, but primarily focused on the following elements:
    • provisioning 
    • internal allocation (sparing quantity and locations)
    • demand forecasting
    • supply planning
    • final disposal (identifying obsolescence)
  • Formulate, plan, & execute supply optimization using mathematical models, planning software, recurring reports, and visualization that provide management the ability to improve operational readiness and asset availability.
  • Draft business case analysis with stated forecasting variables and sensitivity analysis to provide different courses of actions for mission support and sustainment decisions.
  • Develop a working knowledge of modeling and forecasting methodologies, software and programming languages used in the industry.
  • Will learn how to develop project timelines, monitor work completion, and drafting effective communication.  

We invest in the lives of our employees, both in and out of the workplace, by providing competitive pay and benefits packages. Benefits offered may include health care, dental, vision, life insurance; 401(k); education assistance; paid time off including PTO, holidays, and any other paid leave required by law.

EEO Statement

ASRC Federal and its Subsidiaries are Equal Opportunity /Affirmative Action employers. All qualified applicants will receive consideration for employment without regard to race, gender, color, age, sexual orientation, gender identification, national origin, religion, marital status, ancestry, citizenship, disability, protected veteran status, or any other factor prohibited by applicable law.

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