Senior Data Analyst

As a Vision, Mission, and Driven company, VMD has been delivering information technology solutions to the Federal government in Agile Engineering, Cybersecurity, and Critical Infrastructure Protection since 2002. Our mission has now expanded, and we have merged with Xcelerate Solutions to revolutionize end-to-end enterprise security. Together we are committed to protecting our nation’s citizens, critical infrastructure, and resources. Why Join VMD Corp?At VMD, now a part of Xcelerate Solutions, you have the opportunity to thrive in your career and become a Game Changer. The quality and talent of our people is what drives our success. We embrace an employee-first culture and make it a priority to provide professional development opportunities that foster career growth. We help protect American Citizens and the nation’s most critical infrastructure by working alongside our customers and delivering game changing solutions to strengthen their missions. We believe our passion and commitment to achieve our customers' goals and solve their most critical challenges defines who we are. We don’t just dream big, we act on it – through teamwork, dedication, and resilience.

Learn more about VMD culture here: VMD Culture    

Key Functions:

• Data Analyst: 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.

Selected Responsibilities:

• Analyze and define data requirements and specifications.
• 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 and implement data mining and data warehousing programs.
• Develop data standards, policies, and procedures.
• Develop strategic insights from large data sets.
• Effectively allocate storage capacity in the design of data management systems.
• Present data in creative formats.
• Present technical information to technical and nontechnical audiences.
• Program custom algorithms.
• Provide a managed flow of relevant information (via web-based portals or other means) based on mission requirements.
• Provide actionable recommendations to critical stakeholders based on data analysis and findings.
• 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).
• Utilize technical documentation or resources to implement a new mathematical, data science, or computer science method.
• Analyze and plan for anticipated changes in data capacity requirements.
• Manage the compilation, cataloging, caching, distribution, and retrieval of data.
• Provide recommendations on new database technologies and architectures.

 Qualifications and Skills

• Skill in assessing the predictive power and subsequent generalizability of a model.
• Skill in creating and utilizing mathematical or statistical models.
• Skill in data mining techniques (e.g., searching file systems) and analysis.
• Skill in data pre-processing (e.g., imputation, dimensionality reduction, normalization, transformation, extraction, filtering, smoothing).
• Skill in developing data dictionaries.
• Skill in developing data models.
• Skill in developing machine understandable semantic ontologies.
• 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 identifying hidden patterns or relationships.
• Skill in one-way hash functions (e.g., Secure Hash Algorithm [SHA], Message Digest Algorithm [MD5]).
• Skill in performing format conversions to create a standard representation of the data.
• Skill in performing sensitivity analysis.
• Skill in reading Hexadecimal data.
• Skill in Regression Analysis (e.g., Hierarchical Stepwise, Generalized Linear Model, Ordinary Least Squares, Tree-Based Methods, Logistic).
• Skill in the use of design modeling (e.g., unified modeling language).
• 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 binary analysis tools (e.g., Hexedit, command code xxd, hexdump).
• 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 to identify sources, characteristics, and uses of the organization’s data assets.
• Skill in conducting queries and developing algorithms to analyze data structures.
• Skill in generating queries and reports.
• Skill in writing code in a currently supported programming language (e.g., Java, C++).

Required Knowledge

• Knowledge of advanced data remediation security features in databases.
• Knowledge of applications that can log errors, exceptions, and application faults and logging.
• Knowledge of command-line tools (e.g., mkdir, mv, ls, passwd, grep).
• 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 access application programming interfaces (e.g., Java Database Connectivity [JDBC]).
• Knowledge of database management systems, query languages, table relationships, and views.
• Knowledge of database theory.
• Knowledge of digital rights management.
• Knowledge of enterprise messaging systems and associated software.
• Knowledge of how to utilize Hadoop, Java, Python, SQL, Hive, and Pig to explore data.
• Knowledge of Information Theory (e.g., source coding, channel coding, algorithm complexity theory, and data compression).
• Knowledge of interpreted and compiled computer languages.
• Knowledge of low-level computer languages (e.g., assembly languages).
• Knowledge of machine learning theory and principles.
• Knowledge of mathematics (e.g. logarithms, trigonometry, linear algebra, calculus, statistics, and operational analysis).
• 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 secure coding techniques.
• 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 network access, identity, and access management (e.g., public key infrastructure, Oauth, OpenID, SAML, SPML).
• Knowledge of operating systems.
• Knowledge of computer networking concepts and protocols, and network security methodologies.
• Knowledge of cyber threats and vulnerabilities.
• Knowledge of cybersecurity and privacy principles.
• Knowledge of laws, regulations, policies, and ethics as they relate to cybersecurity and privacy.
• Knowledge of risk management processes (e.g., methods for assessing and mitigating risk).
• Knowledge of specific operational impacts of cybersecurity lapses.

Experience:

Senior level positions require seven(7) + years of relevant cyber-security experience and an advanced degree in a technical/cyber-related field. Direct experience or directly relevant certifications may substitute for the academic credentials

Required Abilities

• Ability to accurately and completely source all data used in intelligence, assessment and/or planning products.
• 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).

Citizenship and Clearance: US Citizenship. Must be eligible to pass a FDIC background investigation

Location: Must reside within the DC Metro area. Remote and Contractor Site 1515 Wilson Blvd. Arlington, VA  22209

VMD provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran per applicable Federal, state and local laws. VMD maintains a drug-free workplace.