Data Analytics and AI Associate

Job description and responsibilities

We are looking for an Associate to join our Analytics & AI team and support analytics-driven engagements across a range of industries and business functions.

The role is suited for individuals who are naturally analytical, curious, and comfortable working with data to solve business problems.

You will work with business, financial, customer, operational, and transactional data to identify trends and insights, develop analytical outputs, and support data-driven decision-making. You will also have opportunities to build your capabilities across analytics tools, visualization, automation, and emerging technologies through hands-on project experience.

Educational Background

Bachelor’s degree in a discipline that develops analytical, quantitative, or problem-solving skills. Relevant backgrounds may include, but are not limited to:

• Business or Management
• Accounting or Finance
• Economics
• Statistics or Mathematics
• Data Analytics or Data Science
• Information Technology or Computer Science
• Management Information Systems
• Engineering
• Other related quantitative or analytical disciplines

Technical Foundation

Candidates should have a working knowledge of Microsoft Excel or another spreadsheet-based analytical tool, and a basic foundation in data analysis.

Experience or exposure to one or more of the following is preferred :

• Microsoft Excel or similar spreadsheet tools
• Power BI, Tableau, or other visualization platforms
• Python or R
• Alteryx, Power Query, or similar data preparation and automation tools
• SQL

Required Skills

• Strong quantitative aptitude and comfort working with numerical information and datasets.
• Business curiosity and the ability to understand the context behind the data, not just the numbers themselves.
• Strong analytical and problem-solving ability, with the capacity to break down complex or ambiguous questions into logical analytical steps.
• Ability to identify trends, patterns, anomalies, and relationships in data and assess whether analytical results are reasonable.
• Ability to communicate information analytical findings clearly and concisely to both technical and non-technical audiences through verbal, written, presentation, and visualization skills
• Strong learning agility and willingness to develop proficiency in new analytics tools, methodologies, and technologies.
• High attention to detail and commitment to producing accurate and reliable work.
• Ability to work collaboratively in teams while taking ownership of assigned responsibilities.

Preferred Skills

• Previous experience in data analytics, business intelligence, financial analysis, commercial analysis, consulting, research, reporting, or another analytical role.
• Experience working with large or complex datasets.
• Knowledge of data preparation, data transformation, data modeling, or analytical automation.
• Familiarity with financial, commercial, customer, operational, or transaction-related analysis.
• Experience developing dashboards, reports, data visualizations, or management insights.
• Exposure to AI, generative AI, machine learning, or other emerging analytics technologies.

Key Responsibilities

• Work with structured and unstructured datasets from different business functions and industries.
• Clean, transform, validate, reconcile, and organize data for analysis.
• Perform exploratory and diagnostic analyses to identify trends, patterns, anomalies, relationships, and key business drivers.
• Translate business questions and requirements into appropriate analytical approaches.
• Develop clear and meaningful analytical outputs, including reports, dashboards, visualizations, and presentations.
• Interpret analytical results and communicate key insights, implications, and potential recommendations to project teams and stakeholders.
• Assess data quality and identify limitations, inconsistencies, or gaps that may affect the analysis.
• Support the development and improvement of reusable analytics methodologies, tools, templates, and automated processes.
• Collaborate with cross-functional teams to understand business requirements and deliver analytics solutions that address client or stakeholder needs.
• Stay current with developments in data analytics, visualization, automation, AI, and related technologies.