Data Analytics Specialist

Nestlé; Petaling Jaya; On-site; MYR 60,000 - 90,000; Full time

Job summary

A leading company in the food and beverage sector is seeking a Data Analytics Specialist to analyze complex datasets and deliver insights. The role involves collaboration with business teams, utilizing data visualization tools, and applying data science methods to enhance decision-making processes. Candidates should possess a relevant degree and strong technical skills, including proficiency in programming languages and cloud platforms.

Qualifications

• Experience with cloud platforms and data visualization tools.
• Proficiency in programming languages like Python and R.
• Knowledge of machine learning algorithms and statistical methods.

Responsibilities

• Analyze large datasets and create meaningful visualizations.
• Support data engineering efforts and ensure data quality.
• Communicate analytical outputs clearly using visualization techniques.

Skills

Data Visualization

Analytical Thinking

Collaboration

Machine Learning

Education

Bachelor’s degree in Engineering, Computer Science, Mathematics, Statistics

Tools

MS Power BI

Python

R

Cloud Platforms (Azure, AWS, Google Cloud)

Job description

Joining Nestlé means you are joining the largest Food and Beverage Company in the world. At our very core, we are a human environment – passionate people driven by the purpose of enhancing the quality of life and contributing to a healthier future. A Nestlé career empowers you to make an impact locally and globally, as you are provided with the opportunity to make a mark and stand out, as long as you seek it. With Nestlé, you are enabled and encouraged to grow not only as professionals, but also as people.

We are looking for a Data Analytics Specialist to analyse large, complex datasets, create meaningful visualizations, and deliver insights that empower business teams to make informed decisions. The specialist will also play a significant role in supporting data engineering efforts, ensuring the availability of clean and reliable data through scalable pipelines and robust architectures. Additionally, the role includes experimenting with basic data science methods, such as predictive modelling, clustering, and classification, to uncover hidden patterns and future trends. This hybrid role requires strong technical expertise, a passion for storytelling with data, and the ability to collaborate effectively with business stakeholders and technical teams. The ideal candidate will be adaptable, curious, and capable of integrating analytics, engineering, and data science skills to maximize the value of the organization’s data assets.

A day in the life...

1. Understand business challenges and questions
2. Explore data to find patterns and insights, providing recommendations and driving actions
3. Build capability and ensure consistency of insight generation methodologies for Business Analysts in category/ function
4. Enhance visual outputs and light statistical models leveraging global and local data assets, including machine learning capabilities
5. Maintain last mile reporting applications or local data assets
6. Curate local data assets in cataloguing tools
7. Develop exploratory use cases and coordinate with Global hub for scaling
8. Deliver analytics solutions
9. Use analytical techniques to improve customer and consumer experience, generate revenue, increase margins, and reduce operational costs
10. Leverage industrialized analytical models to increase efficiency
11. Support partners in delivering end-to-end business solutions
12. Communicate analytical outputs clearly using visualization techniques
13. Support KPI/PPI discussions based on analytical results
14. Assist in ad-hoc analyses and present findings clearly
15. Evaluate automation versus manual intervention costs in analytical processes
16. Engage stakeholders and promote analytics best practices
17. Identify opportunities to leverage data assets for business solutions
18. Present business recommendations based on analytics
19. Share best practices within the local analytics community
20. Participate in data science community activities

What will make you successful

1. Bachelor’s degree or higher in Engineering, Computer Science, Mathematics, Statistics, or related fields
2. Experience with cloud platforms (Azure, AWS, Google Cloud)
3. Proficiency in programming languages (Python, R, etc.)
4. Experience with data visualization/BI tools (e.g., MS Power BI)
5. Experience developing light analytical models for business problems
6. Knowledge of machine learning algorithms and statistical methods (regression, clustering, decision trees, neural networks, etc.)
7. Familiarity with analytics project methodologies like CRISP-DM
8. Understanding of FMCG/CPG or Retail industry scenarios
9. Strong visualization skills for dashboards, reports, and insights
10. Excellent written and verbal communication skills
11. Ability to communicate complex results to diverse audiences
12. Ability to work independently
13. Openness to working in a global, virtual team environment