SAIC will be working with AMCOM to develop predictive and descriptive models and dashboards to support decisions in supply chain management, such as demand forecasting and inventory planning. The goal is to leverage AMCOM’s data to derive insights that can improve their efficiency in supplying parts to their customers. The project will start with a focus on the supply chain for Apache Helicopter parts, formulating and proving the methodology to later expand to other systems.
The core components to be developed for the project include: predictive models, dashboards for visualizing results and other data analysis, and back-end software and hosting to support the data pipeline.
The Data Scientist will be a major player in driving the success of this program, which will have great strategic impact for SAIC. He or she will have substantial interaction with the lead data scientist and customer, working with AMCOM, under supervision of the lead data scientist, to determine how best to approach their problems with data science and AI, and consistently communicating technical progress and results. He/She will significantly contribute to the technical effort with the SAIC team, developing predictive models and analysis and collaborating with other data scientists to create visualizations and reports.
• Contributing to the team throughout development of the technical solution, from planning to execution.
• Consults and collaborates with the lead data scientist and customer to ensure that analysis and models address the right questions, shaping the technical vision to satisfy customer needs.
• Develops, tests, and refines predictive models with supply chain data (Ex: demand forecasting, inventory planning).
• Explores and assesses datasets and determines what models, algorithms, and analyses will be most impactful for the customer’s mission, and collaborates with other data scientists to develop them.
• Works with the other data scientists/analysts to develop visualizations, dashboards, and analytic reporting.
- Bachelors and nine (9) years or more experience; Masters and seven (7) years or more experience ; PhD or JD and four (4) years or more experience
• Ability to develop and implement data science solutions from start to finish, through planning and execution.
• Extensive experience developing data science algorithms and advanced models, including supervised and unsupervised machine learning, time series forecasting, and statistical analysis.
• Experience creating meaningful visualizations for analytic results.
• Ability to communicate effectively with both customers and internal team members, including people with varying levels of data science knowledge.
• Experience with common data science tools for algorithm development and visualization: Python, R, SQL, Tableau/PowerBI
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