Data Mining Specialist

Location:

Employment Type:

Department:

About the Role

Data Mining Specialist

Key Responsibilities

1. Data Extraction & Preparation

• Collect, clean, and organise large datasets from multiple sources.
• Develop scripts and queries to extract relevant data efficiently.
• Ensure data quality, consistency, and accuracy for analysis.

2. Data Analysis & Pattern Discovery

• Apply data mining techniques to identify trends, patterns, and correlations.
• Use statistical and machine learning methods to derive insights from structured and unstructured data.
• Interpret results and translate findings into actionable business recommendations.

3. Reporting & Visualisation

• Prepare dashboards, reports, and visualisations to communicate insights to stakeholders.
• Present findings to management, highlighting business implications and opportunities.
• Collaborate with teams to integrate insights into operational or strategic decisions.

4. Collaboration & Support

• Work with cross-functional teams, including Data Engineering, IT, Marketing, and Operations.
• Support predictive analytics, recommendation engines, and optimisation initiatives.
• Provide guidance on data usage and analytical methods for business teams.

5. Continuous Improvement

• Identify opportunities to improve data mining processes, tools, and methodologies.
• Stay updated with emerging data mining techniques, tools, and industry best practices.
• Contribute to automation and efficiency improvements in data analytics workflows.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• 2–5 years of experience in data mining, analytics, or data science roles.
• Strong proficiency in SQL and experience with programming languages such as Python or R.
• Experience with data mining, machine learning, and statistical analysis techniques.
• Ability to interpret complex data and present insights clearly.
• Strong problem-solving skills and attention to detail.

Preferred Skills (Nice-to-have)

• Experience with BI and visualization tools (Power BI, Tableau, Qlik).
• Familiarity with big data platforms (Hadoop, Spark) or cloud data services (AWS, GCP, Azure).
• Knowledge of predictive modeling, clustering, or recommendation algorithms.
• Experience working in B2B, SaaS, finance, or marketing analytics environments.

What We Offer

• Opportunity to work on high-impact data-driven projects.
• Career progression into Senior Data Mining Specialist, Data Scientist, or Data Analytics Lead roles.
• Access to advanced analytics tools and training programs.
• Collaborative and innovative work environment.
• Competitive salary and benefits package.