Job Description

Employment Type: Full time

Position Overview

This role focuses on leveraging data to solve business problems, improve decision-making, and drive value. The ideal candidate will have a strong understanding of data sources, analytics techniques, data visualization, data strategy, and data quality management.

Key Responsibilities and Skills

Data Source Identification

• Knowledge Required:
  • Functional business domain and scenarios
  • Categories of data and their locations
  • Business data requirements
  • Database technologies and distributed datastores (e.g., SQL, NoSQL)
  • Data Quality principles
  • Existing business systems and processes, including key drivers and measures of success
• What you'll do:
  • Support the understanding of priority order of requirements and service level agreements.
  • Identify the most suitable source for data that is fit for purpose.
  • Perform initial data quality checks on extracted data.

Tech Problem Formulation

• Knowledge Required:
  • Analytics, big data analytics, automation techniques and methods
  • Business understanding, precedence, and use cases
  • Business requirements and insights
• What you'll do:
  • Translate co-owned business problems within one's discipline into data-related or mathematical solutions.
  • Identify appropriate methods and tools to provide a solution for the problem.
  • Share use cases and provide examples to demonstrate how the method would solve the business problem.

Data Visualization

• Knowledge Required:
  • Visualization guidelines and best practices for complex data types
  • Multiple data visualization tools (e.g., Python R libraries, GGplot, Matplotlib, Plotly, Tableau, PowerBI)
  • Advanced visualization techniques and tools
  • Multiple story plots and structures
  • OABCDE Communication influencing technique, Emotional intelligence
• What you'll do:
  • Identify and recommend the most suitable visualization tools based on context.
  • Generate appropriate graphical representations of data and model outcomes.
  • Understand customer requirements to design appropriate data representation for complex data sets.
  • Drive User Experience designers and User Interface engineers to build front-end applications.
  • Define application design based on customer requirements.
  • Build compelling stories based on context to integrate multiple pieces of information into cohesive insights.
  • Present to and influence audiences using appropriate data visualization frameworks and convey clear messages through deep business and stakeholder understanding.
  • Customize communication style based on stakeholders and leverage relationships to drive behavioral change.
  • Guide and mentor junior associates on story types, structures, and techniques based on context.

Data Strategy

• Knowledge Required:
  • Understanding of business value and relevance of data and data-enabled insights/decisions.
  • Appropriate application and understanding of the data ecosystem, including Data Management, Data Quality Standards, and Data Governance, Accessibility, Storage, and Scalability.
  • Understanding of the methods and applications that unlock the monetary value of data assets.
• What you'll do:
  • Understand, articulate, interpret, and apply the principles of the defined strategy to unique, moderately complex business problems that may span one or main functions or domains.

Data Quality Management

• Knowledge Required:
  • Data quality management techniques and standards
  • Business metadata definitions and content, data definitions
  • Data profiling tools, data cleansing tools, data integration tools, and issues and event management tools
  • Understanding of users' data consumption, data needs, and business implications
  • Data modeling, storage, integration, and warehousing
  • Data quality framework and metrics
  • User access best practices
  • Enterprise data architecture, modeling and design, storage, integration, and warehousing
  • Enterprise data quality framework and metrics
  • Enterprise data strategy, Enterprise data quality strategy
  • Enterprise strategy to address regulatory and ethical requirements and policies around data privacy, security, storage, retention, and documentation
• What you'll do:
  • Promote and educate others on data quality awareness.
  • Profile, analyze, and assess data quality.
  • Test and validate data quality requirements.
  • Continuously measure and monitor data quality.
  • Deliver against data quality service level agreements.
  • Manage operational Data Quality Management procedures.

Application Instructions

(No specific application instructions were provided in the original text.)

Company Information

(No company information was provided in the original text.)