IT ADI Analyst

Position Snapshot

Location: Malaysia
Company: Nestlé Malaysia
Permanent
Bachelor’s Degree

3+ years experience in an applied analytics role

Position Summary

Joining Nestlé means you are joining the largest Food and Beverage Company in the world. At our very core, weare a human environment – passionate people driven by the purpose of enhancing the quality of life andcontributing to a healthier future. A Nestle 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 Nestle, you are enabled and encouraged to grow not only as professionals, but also as people.

As an IT ADI Analyst, we are looking for professionals who are passionate about deriving actionable insights from data, building predictive models, and contributing to the underlying data infrastructure that powers these efforts.

The core responsibility of the role is to apply advanced data science techniques, such as machine learning, statistical modeling, and algorithm development, to solve complex business challenges. By leveraging tools and frameworks like Python, TensorFlow, or scikit-learn, the role focuses on creating robust, scalable models that can predict trends, optimize processes, and generate significant business value.

In addition to data science, this role incorporates data analytics , requiring expertise in data visualization, KPI tracking, and storytelling with data. The specialist will collaborate with business stakeholders to translate analytical findings into clear, actionable insights presented through interactive dashboards and reports using tools like Power BI or Tableau.

Finally, experience on  data engineering as an added value in supporting the development and maintenance of data pipelines and ensuring the availability of clean, reliable data for both analytics and modeling purposes. Working closely with data engineering teams, this aspect of the role includes tasks like optimizing workflows, implementing ETL processes, and addressing data quality issues.

A day in the life of an IT ADI Analyst

1. Delivery of analytics
      > Use machine learning and predictive analytics to solve complex problems, if applicable.
      > Implement exploratory data analysis (EDA) to discover new opportunities for growth or efficiency.
      > Uses relevant analytical techniques to increase and optimize customer and consumer experience, generate revenue, increase margin, eliminate operational costs and other business outcomes
      > Gain efficiency by leveraging successfully industrialized analytical models that exploit Nestlé's data assets
      > Supports other partners to deliver E2E business solutions (e.g. business domain experts, solution architects, data engineers, visualization experts etc.)
      > Utilizes visualization techniques to clearly communicate the output of analytical processes (descriptive, diagnostic, predictive, prescriptive)
      > Supports KPI/PPI measures discussions from analytical output
      > Considers the cost benefit analysis between full automation and manual intervention in analytical E2E delivery
      > Support local reporting applications or any local data leveraged in market/category
      > Technical and business data curation of local assets in cataloguing tool
      > Develop exploratory use cases and handoff with Global hub if governance decides to scale
2. Stakeholder engagement and analytics evangelisation:
      > Business Acumen: Understand Business Challenge and Business Question
      > Work with business teams to understand requirements and provide data-driven recommendations.
      > Partner with data engineering teams to ensure the availability of clean and reliable data
      > Supports best practice sharing within local analytics community
      > Supports data science community involvment
3. Contribution to business unit strategy under business unit leadership, leveraging the Community of Practice and other relevant networks and experiences.
      > Supports the vision and roadmap for the use of analytics to exploit data as a valued business asset in relation to existing business priorities in order to help business units explore new ways to solve complex business challenges
      > Translates business and data requirements into the appropriate mathematical models and algorithms
      > Proves or invalidates hypotheses as part of a process to construct new analytical methods that can be candidates for Industrialization
      > Works with all relevant stakeholders to support POC/POV and bring it to a closure.

What will make you successful

• Bachelor’s degree or higher in Data Science, Applied Statistics, Mathematics or Relevant tertiary education
• 3+ years experience in an applied analytics role
• Experience in data visualization and statistical techniques and software (e.g., MS Power BI, R, Python, Open source) and cloud  environments (AZURE, AWS, Google Cloud, etc.)
• Experience developing analytical models to solve business problems
• Experience in creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neutral networks, deep learning, optimization, etc
• Knowledge of advance analytics project methodologies like CRISP-DM
• Familiarity with “FMCG/ CPG” or “Retail” industry and applied analytics to scenarios in context of this domain
• Good visualization skills for creating dashboards, scorecards, reports and insights
• Good written and verbal communication skills
• Possess the ability to communicate complex results and insights to technical and non-technical audiences
• Ability to work with minimal supervision
• Open to working in a global environment and with virtual teams
• Good customer facing skills