Serves as a recognized company authority performing system and subsystem definition, preliminary and detailed design, design implementation, and subsystem and system integration and tests for a system. Participates in software requirement review, preliminary and critical design, integration readiness review, and software acceptance review.
This is a challenging position for a mid- to senior-level, data-savvy professional on a project that has real potential to be a game-changer in the client's tool box of expert analytic systems. We're looking for a well-rounded data expert (including data architect, data scientist, data engineer, data analyst) who can enhance mission value by exploiting high volumes of disparate data using the project's suite of cutting-edge tools. This is a hands-on position that requires a self-motivated person who can work in both an unsupervised mode and team mode. This position requires a person who can perform all aspects of data processing and analysis -- including extraction, transformation, and load (ETL) -- to derive valuable insights from the customer's data of all types (structured, unstructured, and semi-structured, but mainly unstructured). This person would be expected to work effectively with the customer help identify patterns, anomalies, and regularities in the data or by applying advanced research skills beyond what the traditional analyst would be expected to use. Being a key data expert, this person would be expected to participate in a wide variety of internal and external for a to advance the analytic tradecraft, improve the capabilities of the project tools, and stay current on the latest trends involving data, such as XML schema changes. This person would also be expected to become a knowledge engineer and be capable of developing the requisite ontologies, taxonomies, lexicons, data specifications, and/or common metadata standards for the project tools and for effective data exchanges with partner systems. This person would be expected to prepare and deliver both technical and high-level briefings on data-related matters that are relevant to the project, including briefings with proposed changes to optimize project use of the data. This person is expected to possess and deliver exceptionally strong technical and ETL skills, because the data-related functions are central to the project's overall success. The ETL tasks encompass the data being cleansed, segmented, normalized, reassembled, harmonized (semantic mediation) and exploited using a variety of extraction and visualization tools. This person could also be expected to participate in the evaluation of new tools for the project, and those tools could range in type from extraction tools to highly sophisticated advanced analytic tools. This person would be expected to possess a natural desire to keep abreast of the latest tools (open source, customer's Proprietary (Equipment, Software), and COTS) for data science/data architecture so that he/she could work effectively with other incubating technologies and help the project identify better capabilities. The project is a joint, R&D effort between the client groups to develop a prototype mass analytic system that will enable users to have sophisticated interactions with large volumes of disparate data, either by presenting the data visually or by asking questions more complex than a Boolean query would allow. The program will feature an immense, spreadsheet-like -œanalytic fabric- of building blocks that will make it easier to integrate with and exploit data from multiple capabilities, such as knowledge bases, natural language processing (NLP) stacks, latent semantic indexing, and visualization tools.
EDUCATION & EXPERIENCE:
Typically requires bachelor's degree or equivalent and 12 to 15 of related experience.
Demonstrated experience interpreting rich data sources, merge data sources together, ensure consistency of data-sets, create visualizations to aid in understanding data, present and communicate the data insights/findings to specialists and scientists in their team and if required to a naive audience. This includes collaborating with non-technical audiences and/or analysts to extract meaning from data and to create data products.
Demonstrated experience of developing analysis and advanced research products by incorporating varying data elements and by building on techniques and theories from many fields, including signal processing, mathematics, probability models, machine learning, statistical learning, computer programming, data engineering, pattern recognition and learning, visualization, uncertainty modeling, data warehousing, and high performance computing.
Demonstrated experience showing, problem-solving skills, flexibility, technical acumen, resourcefulness.
Demonstrated experience with Tableau dashboards and Impala tables
Holds a Bachelor's degree or equivalent in computer science, data science, data architecture, data analysis, or related field of study.
Demonstrated experience of using SQL
Demonstrated ability of using data science techniques to conduct research across various domains, including the political science, economics, social sciences and the humanities.
Holds a Master's degree or Ph.D in data science, data architecture, data analysis, or related field of study.
Demonstrated experience creating a data model that effectively integrates mission needs with underlying data structures. This includes experience with developing a complete data taxonomy, ontology, or metadata standard from scratch as well as merging two data specifications from differing projects.
Demonstrated experience of being embedded with an the Sponsor's mission customer to exploit data science techniques in a collaborative manner, including briefing the mission customer and its analysts.
Demonstrated experience of working with conventional tools for Big Data and Data Science, such as Big Data manipulation tools (e.g. Hadoop, Pig, Hive, Python) or statistical analysis tools (e.g. SAS, SPSS, R), or data warehouse and loading tools (e.g. Teradata, Informatica).
Demonstrated experience with 1010data Appliance, entity extraction tools (e.g. Aerotext, NetOwl), and/or Digital Reasoning Synthesis (DRS), or other similar advanced computing systems, such as those involving natural language processing or advanced analytics.
Demonstrated experience with designing, testing and deploying Tableau dashboards and/or other user interface (U/I) features for data scientists or analysts with this client or customer's partners.
Demonstrated experience with client's or customer's partners data architecture constructs, including metadata standards, PUBS-XML, NewsML, or comparable XML formats.
Demonstrated and recognized expertise in the field of data science, such as by authoring papers on data science, speaking at conventions, or leading other initiatives in data science, machine learning, or related fields.
Minimum of two years of demonstrated experience as a data expert (data analyst, data scientist, data architect) with client or r's partners. ITAHP
Normal demands associated with an office environment. Ability to work on computer for long periods, and communicate with individuals by telephone, email and face to face. Some travel may be required.