This role uses Data Science and Engineering techniques to satisfy customer requirements. This role evaluates and uses algorithms for Natural Language Processing (NLP), Artificial Intelligence (AI), and Machine Learning (ML). This role develops scripts, notebooks or applications (using Python or Java and associated libraries or frameworks: Scikit-Learn, Numpy, Tensorflow, Pytorch, Spark, Spark MLlib, H20.ai, etc.) that utilize, collect, aggregate and clean large data sets to perform analysis, clustering, entity resolution and structured information extraction for work products. Models are trained and refined using these tools and evaluated for effectiveness using appropriate criteria/metrics for the task. This role collaborates across a team of Data Scientists, Data Administrators, Software and Data Engineers to produce work products.
- This role designs and develops methods, processes, and systems to consolidate and analyze structured and unstructured, diverse sources including big data sources.
- This role will concentrate on the AI discipline of Machine Learning - in data, pattern identification and analysis. As such will be evaluate capabilities and analysis in Natural Language Processing, Machine Learning, predictive modeling, statistical analysis and hypothesis testing
- This role develops and uses advanced software programs, algorithms, query techniques, model complex business problems, and automated processes to cleanse, integrate, and evaluate datasets.
- Works with cross-discipline teams to ensure connectivity between various data sources and business problems.
- Identifies meaningful insights and interprets and communicates findings and recommendations.
- This role develops algorithms and analytical techniques to improve business performance.
- Maintains awareness of emerging analytics and big-data technologies.
- Master's degree in engineering, computer science, or other related technical field or Bachelor's degree in a business or management-related field accompanied by experience managing technical requirements in complex programs.
- Candidate must have in-depth experience in Machine Learning
- Experience developing Random Forests decision trees and subsequent analysis.
- Demonstrated experience with Splunk and deployment methodologies
- Demonstrated experience negotiating complex scenarios and challenges and devising courses of action to resolve situations with predictable outcomes.
- Experience supporting critical objectives where decisions impacts on outcomes.
- Candidate must have Bachelors with 8-12 years of prior relevant experience or Masters with 6-10 years of prior relevant experience.
- Candidate must have an active TS/SCI with polygraph to be considered for this position.
- Experience with R and MapReduce