Responsibilities
• Directing the data gathering, data mining, and data processing processes in huge volume; creating appropriate data models.
• Exploring, promoting, and implementing semantic data capabilities through Natural Language Processing, text analysis and machine learning techniques.
• Leading to define requirements and scope of data analyses; presenting and reporting possible business insights to management using data visualization technologies.
• Conducting research on data model optimization and algorithms to improve effectiveness and accuracy on data analyses.
Skill Descriptors
Business Statistics: Knowledge of the statistical tools, processes, and practices to describe business results in measurable scales; ability to use statistical tools and processes to assist in making business decisions.
Level Working Knowledge:
• Explains the basic decision process associated with specific statistics.
• Works with basic statistical functions on a spreadsheet or a calculator.
• Explains reasons for common statistical errors, misinterpretations, and misrepresentations.
• Describes characteristics of sample size, normal distributions, and standard deviation.
• Generates and interprets basic statistical data.
Accuracy and Attention to Detail: Understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision.
Level Extensive Experience:
• Evaluates and makes contributions to best practices.
• Processes large quantities of detailed information with high levels of accuracy.
• Productively balances speed and accuracy.
• Employs techniques for motivating personnel to meet or exceed accuracy goals.
• Implements a variety of cross-checking approaches and mechanisms.
• Demonstrates expertise in quality assurance tools, techniques, and standards.
Analytical Thinking: Knowledge of techniques and tools that promote effective analysis; ability to determine the root cause of organizational problems and create alternative solutions that resolve these problems.
Level Working Knowledge:
• Approaches a situation or problem by defining the problem or issue and determining its significance.
• Makes a systematic comparison of two or more alternative solutions.
• Uses flow charts, Pareto charts, fish diagrams, etc. to disclose meaningful data patterns.
• Identifies the major forces, events and people impacting and impacted by the situation at hand.
• Uses logic and intuition to make inferences about the meaning of the data and arrive at conclusions.
Machine Learning: Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.
Level Working Knowledge:
• Completes specific tasks and initiatives utilizing machine learning technologies, such as search engine optimization.
• Utilizes specific tools and techniques to process descriptive and inferential statistics.
• Applies specific computing languages and tools in machine learning, such as R and Python.
• Explores to use machine learning in one own areas to make business improvements.
• Conducts data mining and cleaning initiatives.
Programming Languages: Knowledge of basic concepts and capabilities of programming; ability to use tools, techniques and platforms in order to write and modify programming languages.
Level Working Knowledge:
• Participates in the implementation and support of specialized programming languages.
• Conducts basic reviews on writing a specific programming language within a specific platform.
• Assists with the design and development of specialized programming languages.
• Follows an organization's standards, policies and guidelines for structured programming specifications.
• Diagnoses and reports minor or routine programming language problems.
Query and Database Access Tools: Knowledge of data management systems; ability to use, support and access facilities for searching, extracting and formatting data for further use.
Level Extensive Experience:
• Writes, debugs and implements complex queries involving multiple tables or databases.
• Works with aggregate functions, complex joins, groupings, dynamic and embedded SQL's (Structured Query Languages).
• Teaches others about query optimization techniques and facilities.
• Consults on query optimization, interactive queries, testing and verification.
• Evaluates all major database access tools and functions for distributed databases.
• Compares and contrasts the benefits and drawbacks of various SQL products.
Requirements Analysis: Knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyze and record required business functionality and non-functionality requirements to ensure the success of a system or software development project.
Level Working Knowledge:
• Follows policies, practices and standards for determining functional and informational requirements.
• Confirms deliverables associated with requirements analysis.
• Communicates with customers and users to elicit and gather client requirements.
• Participates in the preparation of detailed documentation and requirements.
• Utilizes specific organizational methods, tools and techniques for requirements analysis.