Data Analyst

Role Definition

Performs analytical tasks and initiatives on huge amount of data to support data-driven business decision and development.

Responsibilities

• Direct the data gathering, data mining, data processing and data modelling for large datasets including the processing, cleansing, and verification of datasets used for analysis. .
• Lead requirement definition and scope of data analyses, presenting and reporting possible business insights to management using data visualization technologies.
• Conduct research on data model optimization and algorithms to improve effectiveness and accuracy on data analyses.
• Use knowledge of statistical approaches, data management techniques, and/or related digital technologies to complete projects.
• Conduct technical analysis of new requests from internal customers to gather requirements, analyses, and convert into technical requirements for optimal coding structure for technical development.
• Research and apply new methods and digital technologies to exceed customer expectations.

Background/Experience :

• Bachelors degree with minimum of 2+ years experience in Data Analytics.
• The applicant must have employment experience with Power BI, Tableau , Power Automate, Power App, snowflake, SQL, Python & Data Visualization.
• Ability to clearly communicate vision and complex technical ideas, data science initiatives and insights to all levels of users within the organization
• 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.
• Knowledge of tools, methods, and techniques of requirement analysis; ability to elicit, analyse and record required business functionality and non-functionality requirements to ensure the success of a system or software development project.

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 Basic Understanding:

Identifies and describes basic statistical measures.

Summarizes the underlying uncertainties associated with statistical analysis and reporting.

Describes the relationship between statistical measurement and continuous improvement.

Cites examples and meaning of statistics used in own area.

Accuracy and Attention to Detail: Understanding the necessity and value of accuracy; ability to complete tasks with high levels of precision.

Level Working Knowledge:

Accurately gauges the impact and cost of errors, omissions, and oversights.

Utilizes specific approaches and tools for checking and cross-checking outputs.

Processes limited amounts of detailed information with good accuracy.

Learns from mistakes and applies lessons learned.

Develops and uses checklists to ensure that information goes out error-free.

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 Basic Understanding:

Names specific tools or techniques that can be used to support the analytical thinking process.

Describes specific software applications or products used for business analytics.

Gives examples of how analytical thinking has been used to resolve problems.

Helps others research and learn more about business analytics tools and applications.

Machine Learning: Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.

Level Basic Understanding:

Explains the definition and objectives of machine learning.

Describes the algorithms and logic of machine learning.

Distinguishes between machine learning and deep learning.

Gives several examples on the implementation of machine learning.

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 Basic Understanding:

Describes the basic concepts of programming and program construction activities.

Uses programming documentation including program specifications in order to maintain standards.

Describes the capabilities of major programming languages.

Identifies locally relevant programming tools.

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 Basic Understanding:

Identifies query facilities that are available in one's own environment.

Explains organization's standards, procedures and practices for building queries.

Describes the functions and features of query and database access tools.

Identifies the key benefits and drawbacks of query languages.

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.