ASRC Federal Holding Company
Data Scientist, US Citizenship Required
ASRC Federal Holding Company, Elizabeth City, North Carolina, us, 27906
Job Description
ASRC Federal Agile Decision Sciences is seeking a
Data Analyst/Logistician
with a desire and aptitude to learn
SAS, Python or "R"
insupport of the US Coast Guard BOD ALC (Aviation Logistics Center) and their mission of keeping aircraft maintained and serviced so those serving in the Coast Guard can keep our country safe. The Aviation Logistics Center's mission includes Depot Level Maintenance, Engineering, Supply, Procurement and Information Services.
Responsibilities:
Experience leveraging automation and artificial intelligence available in data analysis tools (SAS Viya) to enhance data visualization and possible machine learning.Experience providing business case analysis with stated planning variables and sensitivity analysis for different courses of actions for mission support and sustainment decisions.Function as the BOD Logistics Team Liaison to the production line Divisions to ensure BOD output data/reports properly represents the production lines coupled to the ALC mission.Formulate, plan, execute supply optimization using mathematical models, planning software, recurring reports, white papers, and dashboards that provide management the information required to effectively allocated resources and execute procurements that provide the greatest return on investment to operational readiness and asset availability.Create a Logistical Analysis program that has clearly defined processes and procedures to build out customer requirements, evaluate/prioritize work acceptance, document application development, regularly re-evaluate product support.Analyze and coordinate the logistical functions of DCMS (Deputy Commandant for Mission Support). Responsible for the evaluating the entire life cycle of a product, but primarily focused on the following elements:
acquisition (funding requirements and contract candidates)internal allocation (sparing quantity and locations) o final disposal (identifying obsolescence)Secondary focus on distribution and delivery as needed to support other DCMS entities.Experience in evaluating the entire life cycle of a product but focused on these elements:provisioning/ internal allocation (sparing quantity and locations) / demand forecasting / supply planning / final disposal (identifying obsolescence)Working knowledge of latest advanced modeling and forecasting methodologies, software, and programming languages used in Industry to provides recommendations for improvement to current models, forecasts, and tools.Establish project timelines, monitor work completion, and provide assistance to other Logisticians to improve project management, breadth of analysis, and communication skills.
Requirements
ASRC Federal offers an excellent salary and benefits package that includes certification reimbursement and a matching 401k with immediate vesting. We foster a climate of professional development and recognition for excellence. Find out why we were certified consistently as a "Great Place to Work".
Education/Experience:
Bachelor's degree and eight(8) years of experience inLogistics Data Management/Analyst related work with proficiency in SAS OR a Master's degree and six (6) years of experience in Logistics Data Management/Analyst related work.In lieu of a degree, ten (10) years of Logistics Data Management/Analyst experience is acceptable.Degrees in Computer/Data Science, Mathematics, Logistics-Supply Chain, Analytics-Statistics, Engineering, Information Systems, Or other strongly related fields are desired.US Citizenship is required for this position and the ability to obtain an EOD (Entry on Duty) from Department of Homeland Security.
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.
ASRC Federal Agile Decision Sciences is seeking a
Data Analyst/Logistician
with a desire and aptitude to learn
SAS, Python or "R"
insupport of the US Coast Guard BOD ALC (Aviation Logistics Center) and their mission of keeping aircraft maintained and serviced so those serving in the Coast Guard can keep our country safe. The Aviation Logistics Center's mission includes Depot Level Maintenance, Engineering, Supply, Procurement and Information Services.
Responsibilities:
Experience leveraging automation and artificial intelligence available in data analysis tools (SAS Viya) to enhance data visualization and possible machine learning.Experience providing business case analysis with stated planning variables and sensitivity analysis for different courses of actions for mission support and sustainment decisions.Function as the BOD Logistics Team Liaison to the production line Divisions to ensure BOD output data/reports properly represents the production lines coupled to the ALC mission.Formulate, plan, execute supply optimization using mathematical models, planning software, recurring reports, white papers, and dashboards that provide management the information required to effectively allocated resources and execute procurements that provide the greatest return on investment to operational readiness and asset availability.Create a Logistical Analysis program that has clearly defined processes and procedures to build out customer requirements, evaluate/prioritize work acceptance, document application development, regularly re-evaluate product support.Analyze and coordinate the logistical functions of DCMS (Deputy Commandant for Mission Support). Responsible for the evaluating the entire life cycle of a product, but primarily focused on the following elements:
acquisition (funding requirements and contract candidates)internal allocation (sparing quantity and locations) o final disposal (identifying obsolescence)Secondary focus on distribution and delivery as needed to support other DCMS entities.Experience in evaluating the entire life cycle of a product but focused on these elements:provisioning/ internal allocation (sparing quantity and locations) / demand forecasting / supply planning / final disposal (identifying obsolescence)Working knowledge of latest advanced modeling and forecasting methodologies, software, and programming languages used in Industry to provides recommendations for improvement to current models, forecasts, and tools.Establish project timelines, monitor work completion, and provide assistance to other Logisticians to improve project management, breadth of analysis, and communication skills.
Requirements
ASRC Federal offers an excellent salary and benefits package that includes certification reimbursement and a matching 401k with immediate vesting. We foster a climate of professional development and recognition for excellence. Find out why we were certified consistently as a "Great Place to Work".
Education/Experience:
Bachelor's degree and eight(8) years of experience inLogistics Data Management/Analyst related work with proficiency in SAS OR a Master's degree and six (6) years of experience in Logistics Data Management/Analyst related work.In lieu of a degree, ten (10) years of Logistics Data Management/Analyst experience is acceptable.Degrees in Computer/Data Science, Mathematics, Logistics-Supply Chain, Analytics-Statistics, Engineering, Information Systems, Or other strongly related fields are desired.US Citizenship is required for this position and the ability to obtain an EOD (Entry on Duty) from Department of Homeland Security.
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.