, programmatic, strategic, and operational analysis.
Explain analytics model behavior/results in the vernacular of business.
Perform technical risk analysis and reliability assessments.
Perform multiple forms of advanced analyses, sustainment, optimization, text analytics, machine learning, parametric and non-parametric statistical models and techniques
Build, test, validate and demonstrate analytical models through various relevant error metrics and calibration techniques
Provide recommendations for plans, programs, strategies, policies and budgets.
Design algorithms that require a number of different models/methods to be used in an ensemble
Deploy models into production
Artificial Intelligence & Data Engineering
In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment.
The Artificial Intelligence & Data Engineering team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. Together with the Strategy practice, our Strategy & Analytics portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets.
Artificial Intelligence & Data Engineering will work with our clients to:
Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms
Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions
Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements
3+ years of experience to have great understanding on the ML lifecycle and concepts
3+ years of experience with the design and implementation (building, containerizing, and deploying end to end automated data and ML pipelines) of automated cloud solutions
3+ years of experience in developing algorithms using data science technologies to build analytical models
3+ years of data extraction/manipulation experience using scripts specific to AI/ML
3+ years of IT experience. Minimum 2 years of relevant experience delivering AI/ML projects
3+ years of modeling experience using a variety of regression and supervised and unsupervised learning techniques.
3+ years of experience in data wrangling/cleansing, statistical modeling, and programming
3+ years of extensive experience working in an Agile development environment
3+ years of experience for fluency in both structured and unstructured data (SQL, NOSQL)
3+ years of production experience with Apache Spark
3+ years of hands-on experience with web APIs, CI/CD for ML, and Serverless Deployment
2+ years of experience with presentation and data analysis software such as: SAS, R, SPSS, MATLAB, QlikView, Excel and Access
1+ years of experience to have familiarity with Linux OS and Windows servers
1+ years of experience to have knowledge of Docker, Jenkins, Kubernetes, and other DevOps tools
o Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
Must be a US Citizen
Must live near, or relocate to, the Lake Mary, FL; Gilbert, AZ; or Mechanicsburg, PA areas
Must be in your designated office location 10%-30% throughout the year
Ability to travel up to 10%, on average, based on the work you do and the clients and industries/sectors you serve
Bachelor's degree, preferably in Computer Sciences, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience