Figure Eight Federal (F8F): Leading the Future of AI Training Data Figure Eight Federal (F8F) is the FOCI mitigated arm of Appen (APXYY) focused on the U.S. defense and intelligence sector. As a global leader in the development and optimization of AI training data, F8F sets the standard for innovation in quality, efficiency, and scalability across AI initiatives.
Our technology is utilized by over 6.8 million data specialists skilled in over 235 languages, delivering unparalleled expertise in capturing domain specific knowledge into formats models can train against. The F8F platform is currently used by over 80% of leading LLM developers.
As the world's largest provider of geospatial human domain monitoring data, F8F processes and analyzes petabits worth of geospatial data to provide enhanced situational awareness around the globe. Through our Hydra AI platform, we handle more than 500 billion events per month across 200 countries and territories, serving over 1 billion active users.
At its core, F8F is dedicated to empowering defense and intelligence agencies with cutting-edge technology to drive the Nation's strategic AI advantage and drive mission impacts. With a proven track record of delivering secure, reliable, and scalable data solutions, F8F remains at the forefront of driving innovation in AI training data.
Learn more about how F8F is shaping the future of AI at F8Federal.com.
The data scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.
\n Responsibilities:Produce data visualizations that provide insight into dataset structure and meaningCollaborate with subject matters experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats (e.g., SQL tables, structured metadata, network logs)Incorporate SME input into feature vectors suitable for analytic development and testingTranslate customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypesDevelop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analyticsDevelop statistical tests to make data-driven recommendations and decisionsDevelop experiments to collect data or models to simulate data when required data are unavailableDevelop feature vectors for input into machine learning algorithmsIdentify the most appropriate algorithm for a given dataset and tune input and model parametersEvaluate and validate the performance of analytics using standard techniques and metrics (e.g. cross validation, ROC curves, confusion matrices)Evaluate individual analytic efforts and make recommendations in the analytic development processRecommend solutions that can scale to large datasetsCollaborate with software engineers, cloud developers, and appropriate stakeholders to develop production analyticsDevelop and train machine learning systems based on statistical analysis of data characteristics to support mission automation Required Skills:Requires a bachelor's degree in a relevant discipline (e.g., statistics, mathematics, operations research, engineering, or computer science) from an accredited college or universityEight (8) years of relevant experience analyzing datasets and developing analyticsFive (5) years of relevant experience programming with data analysis software such as R, Python, SAS, or MATLABMaster's degree in relevant discipline may be substituted for two (2) years of relevant experience reducing the requirement to six (6) years of relevant experience analyzing datasets and developing analytics, and three (3) years of relevant experience programming with data analysis software such as R, Python, SAS, or MATLAB. A PhD in relevant discipline may be substituted for four (4) years relevant experience reducing the requirement to four (4) years of relevant experience analyzing datasets and developing analytics, and one (1) year of experience programming with data analysis software such as R, Python, SAS, or MATLAB. In lieu of a bachelor's degree, an additional four (4) years of relevant experience may be substituted for a total of twelve (12) years of relevant experience analyzing datasets and developing analytics, and nine (9) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.ACTIVE, CURRENT SECURITY CLEARANCE
\n$1 - $200 a year
\nWe are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.