Senior Data Analyst / Data Scientist

Foto-Zzoom Sdn Bhd; Kuala Lumpur; On-site; MYR 250,000 - 300,000; Full time

Job summary

A data insights company in Kuala Lumpur is seeking a Data Analyst to collect, clean, and analyze vast datasets. The ideal candidate will have a bachelor's degree and 3+ years of experience, proficient in SQL, Python, and data visualization tools. This role offers a challenging environment to generate insights for operational efficiency and strategic advantages. You will work closely with various teams to promote data-driven decision-making across the organization.

Qualifications

• Minimum of 3 years of experience in data analysis or business intelligence.
• Familiarity with data warehousing concepts and ETL processes.

Responsibilities

• Collect, clean, and analyze large datasets.
• Develop and maintain dashboards and reports.
• Ensure data accuracy and integrity.

Skills

Strong analytical skills

Excellent communication skills

Proficient in SQL

Knowledge of Python

Experience with Tableau

Predictive modeling

Attention to detail

Education

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science

Tools

Power BI

Data visualization tools

Job description

Data Extraction and Analysis

• Collect, clean, and analyze large datasets related to operations, commerce, user behaviors, retention, operational efficiencies, user experience, employee experience, redundancies, and more.
• Utilize statistical methods and tools to interpret data sets, paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics.

Commercial and Non-Commercial Insights

• Focus on commercial data (marketing, sales) to provide insights on customer acquisition, retention, revenue growth, and market trends.
• Analyze non-commercial data (operations, maintenance, customer advocacy, inventory) to identify areas for operational improvements and efficiency gains.
• Reporting and Visualization:
  • Develop and maintain dashboards, reports, and visualizations to effectively communicate findings to management and stakeholders.
  • Present complex information in a clear and concise manner, making data accessible and understandable to non-technical team members.

Proactive Insight Generation

• Go beyond management's requests to identify and explore data-driven opportunities and challenges not previously considered.
• Provide inferential insights that can lead to strategic advantages and operational enhancements, highlighting areas that may not be immediately apparent.

Industry and Market Analysis

• Gather and analyze industry data to understand market dynamics, competitor performance, and external factors affecting the business.
• Use external data sources to augment internal data, providing a comprehensive view that aids in strategic planning and decision-making.

Data Integrity and Compliance

• Ensure data accuracy and integrity by performing regular audits and validation checks.
• Adhere to data privacy regulations and company policies when handling sensitive information.

Collaboration and Accountability

• Work closely with cross-functional teams, including marketing, operations, maintenance, HR, and management, to support their data needs.
• Help teams understand the implications of data insights for their areas, promoting data-driven decision-making across the organization.
• Contribute to holding teams accountable by providing transparent and actionable data.

Education and Experience

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
• Minimum of 3 years of experience in data analysis, business intelligence, or a similar role.
• Proficiency in data analysis tools and languages such as SQL, Python, R, and experience with data visualization tools like Tableau or Power BI.
• Familiarity with data warehousing concepts and ETL processes.

Skills and Abilities

• Analytical Expertise: Strong analytical skills with the ability to interpret complex datasets and translate findings into actionable insights.
• Commercial Acumen: Understanding of both commercial (marketing, sales) and non-commercial (operations, maintenance) aspects of the business.
• Technical Proficiency: Experience with statistical analysis, predictive modeling, and data mining techniques.
• Communication Skills: Excellent verbal and written communication skills, with the ability to present data findings to non-technical audiences effectively.
• Problem-Solving: Proactive in identifying issues and opportunities within the data, providing solutions that align with business objectives.
• Attention to Detail: Meticulous in ensuring data accuracy and integrity.
• Industry Awareness: Knowledge of industry trends and the ability to leverage external data sources for comprehensive analysis.

Personal Attributes

• Resilience: You believe there's always a solution and persistently seek answers through data.
• Growth Mindset: Fully committed to personal and professional development, staying updated with the latest data analytics tools and methodologies.
• Profitability Focus: Understand how data insights can drive profitability and operational efficiency.
• Results-Oriented: Dedicated to delivering high-quality outcomes that make a tangible impact.
• Long-Term Vision: Provide data solutions that contribute to lasting success and sustainability.
• Curiosity and Innovation: A natural inclination to explore data creatively, uncovering hidden patterns and insights.
• Integrity and Ethics: Maintains confidentiality and handles sensitive data responsibly.
• Collaboration: Works effectively with various teams, fostering a culture of data-driven decision-making.
• Adaptability: Comfortable navigating changing priorities and adapting to new analytical tools or methodologies.
• Data Modeling and Interpretation: Expertise in creating models that predict trends and inform strategic decisions.
• Data Visualization: Ability to present data in engaging and understandable formats.
• Business Intelligence: Apply data insights to improve business processes, customer experience, and operational efficiency.
• Technical Proficiency: Skilled in using advanced analytical tools and staying abreast of technological advancements in data analytics.

Note

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