Examines data from multiple disparate sources with the goal of providing security and privacy insight. Designs and implements custom algorithms, workflow processes, and layouts for complex, enterprise-scale data sets used for modeling, data mining, and research purposes.
Knowledge of computer networking concepts and protocols, and network security methodologies.
Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).
Knowledge of laws, regulations, policies, and ethics as they relate to cybersecurity and privacy.
Knowledge of cybersecurity and privacy principles.
Knowledge of cyber threats and vulnerabilities.
Knowledge of specific operational impacts of cybersecurity lapses.
Knowledge of computer algorithms.
Knowledge of computer programming principles
Knowledge of data administration and data standardization policies.
Knowledge of data mining and data warehousing principles.
Knowledge of database management systems, query languages, table relationships, and views.
Knowledge of digital rights management.
Knowledge of enterprise messaging systems and associated software.
Knowledge of low-level computer languages (e.g., assembly languages).
Knowledge of mathematics (e.g. logarithms, trigonometry, linear algebra, calculus, statistics, and operational analysis).
Knowledge of network access, identity, and access management (e.g., public key infrastructure, Oauth, OpenID, SAML, SPML).
Knowledge of operating systems.
Knowledge of policy-based and risk adaptive access controls.
Knowledge of programming language structures and logic.
Knowledge of query languages such as SQL (structured query language).
Knowledge of sources, characteristics, and uses of the organization's data assets.
Knowledge of the capabilities and functionality associated with various technologies for organizing and managing information (e.g., databases, bookmarking engines).
Knowledge of command-line tools (e.g., mkdir, mv, ls, passwd, grep).
Knowledge of interpreted and compiled computer languages.
Knowledge of secure coding techniques.
Knowledge of advanced data remediation security features in databases.
Skill in identifying common encoding techniques (e.g., Exclusive Disjunction [XOR], American Standard Code for Information Interchange [ASCII], Unicode, Base64, Uuencode, Uniform Resource Locator [URL] encode).
Skill in assessing the predictive power and subsequent generalizability of a model.
Skill in data pre-processing (e.g., imputation, dimensionality reduction, normalization, transformation, extraction, filtering, smoothing).
Skill in identifying hidden patterns or relationships.
Skill in performing format conversions to create a standard representation of the data.
Skill in performing sensitivity analysis.
Skill in developing machine understandable semantic ontologies.
Skill in Regression Analysis (e.g., Hierarchical Stepwise, Generalized Linear Model, Ordinary Least Squares, Tree-Based Methods, Logistic).
Skill in transformation analytics (e.g., aggregation, enrichment, processing).
Skill in using basic descriptive statistics and techniques (e.g., normality, model distribution, scatter plots).
Skill in using data analysis tools (e.g., Excel, STATA SAS, SPSS).
Skill in using data mapping tools.
Skill in using outlier identification and removal techniques.
Skill in writing scripts using R, Python, PIG, HIVE, SQL, etc.
Skill in the use of design modeling (e.g., unified modeling language).
Skill to identify sources, characteristics, and uses of the organization's data assets.
Ability to build complex data structures and high-level programming languages.
Ability to dissect a problem and examine the interrelationships between data that may appear unrelated.
Ability to identify basic common coding flaws at a high level.
Ability to use data visualization tools (e.g., Flare, HighCharts, AmCharts, D3.js, Processing, Google Visualization API, Tableau, Raphael.js).
Ability to accurately and completely source all data used in intelligence, assessment and/or planning products.
Analyze and define data requirements and specifications.
Analyze and plan for anticipated changes in data capacity requirements.
Develop data standards, policies, and procedures.
Manage the compilation, cataloging, caching, distribution, and retrieval of data.
Provide a managed flow of relevant information (via web-based portals or other means) based on mission requirements.
Provide recommendations on new database technologies and architectures.
Analyze data sources to provide actionable recommendations.
Assess the validity of source data and subsequent findings.
Collect metrics and trending data.
Conduct hypothesis testing using statistical processes.
Confer with systems analysts, engineers, programmers, and others to design application.
Develop and facilitate data-gathering methods.
Develop strategic insights from large data sets.
Present technical information to technical and nontechnical audiences.
Present data in creative formats.
Program custom algorithms.
Provide actionable recommendations to critical stakeholders based on data analysis and findings.
Utilize technical documentation or resources to implement a new mathematical, data science, or computer science method.
Effectively allocate storage capacity in the design of data management systems.
Read, interpret, write, modify, and execute simple scripts (e.g., Perl, VBScript) on Windows and UNIX systems (e.g., those that perform tasks such as: parsing large data files, automating manual tasks, and fetching/processing remote data).
Utilize different programming languages to write code, open files, read files, and write output to different files.
Utilize open source language such as R and apply quantitative techniques (e.g., descriptive and inferential statistics, sampling, experimental design, parametric and non-parametric tests of difference, ordinary least squares regression, general line).
Develop and implement data mining and data warehousing programs.
Privacy & Cookies Policy
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.