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.