Data Analyst at Kapa Oil Refineries Limited

We are looking for a talented and motivated individual to join us in a Data Analyst at Kapa Oil Refineries Limited Role. This is an exciting opportunity to make a meaningful impact while growing your skills and contributing to a dynamic team. If you’re passionate about this and eager to take on new challenges, we want to hear from you!

OBJECTIVES:

To analyze and interpret company data, delivering actionable insights to support strategic decision-making and operational efficiency for Kapa Oil

QUALIFICATIONS

Bachelor’s Degree in Mathematics, Economics, Computer science, Information system or Statistics.

EXPERIENCE

Minimum of 4 years experience as a Data analyst

SKILLS/ KNOWLEDGE

Strategic outlook
Technical expertise in data models, database design development, data mining, and segmentation techniques.
Proficiency with open source reporting packages like Superset, databases like SQL, SAP HANA, MY SQL, Python and programming languages like XML, SPSS, SAS, JavaScript, ETL frameworks, Power BI/Tableau.
Meticulous in analyzing and validating data to ensure accuracy and reliability.
Excellent Communicator: Can translate complex data into clear, concise insights for both technical and non-technical audiences.
Team Collaborator: Engages effectively with cross-functional teams to understand and meet their data needs.
Problem Solver: Adept at identifying business challenges through data and providing actionable solutions.

Reports To Senior Management

Data Analysis & Reporting:

Create detailed reports and dashboards summarizing trends, patterns, and actionable insights across all company data streams.
Deliver weekly and monthly insights that improve operational efficiency and enhance decision making.

Performance Metrics:

Identify and track KPIs across departments (sales, supply chain, production, and marketing).
Provide real-time analysis of performance against targets and suggest corrective actions.

Predictive Analytics:

Utilize advanced statistical techniques and predictive modelling to forecast market trends, consumer behaviour, and internal operational needs.
Deliver quarterly presentations on trends and forecasts to the management team.

Data Integrity & Management:

Ensure the accuracy, consistency, and security of company data across systems.
Collaborate with IT to develop and implement databases, data collection systems and analytics strategies to optimize statistical efficiency and quality

Stakeholder Collaboration:

Work closely with department heads to understand their data requirements and provide tailored insights.
Lead cross-functional training sessions to enhance data literacy within the organization.
To locate and define new process improvement opportunities