Data Science & Engineering Internship-Unilever

  • Internship
  • Nairobi


Job Description

Team Responsibilities:

The Unilever Africa Data and Analytics team is a diverse group comprising actuaries, accountants, mathematicians, data scientists, engineers, economists, statisticians, and other specialists. This team offers valuable insights and expertise across our business sectors. Using our varied skill sets, we drive business value by innovating solutions through advanced analytical modeling (ML & AI), robotic process automation, and analytics in finance, customer service, and marketing. Our team adapts to different technologies and platforms tailored to the needs of each business unit. We are collaborative, and engaging, and actively seek motivated and high-achieving individuals.

Our team manages data, analytics, and insights demands, streamlining related processes for efficient insights generation. We utilize tools from the Global D&A team to provide seamless, fast insights through automation and consolidation.

Main Job Purpose:

Data is the foundation of our organization’s transformation into a data-intelligent business. Joining our Internship program at this juncture is especially exciting. The fast-moving consumer goods (FMCG) sector is rapidly evolving, and we’re leading this transformation in data analytics. We’re aligning our workplaces and teams to swiftly meet the evolving needs of the business and customers. The demand for data science and engineering skills often outpaces supply across the continent. In addition to traditional FMCG competitors, we now face competition from startups offering flexible “gig” work. Attracting and retaining data science and engineering talents is a prevalent challenge. Therefore, establishing a steady skills pipeline is imperative.

As we shape ourselves into a ‘start-up’ with a century of heritage, we are implementing significant changes to meet people, business, and customer requirements. Our culture is dynamic, fostering rapid learning, and tailored for those who want to enhance their data science and engineering skills alongside core business skills. We are dedicated to Africa and its growth.

This 24-month Internship program is a transformative journey that enhances skills and capabilities while maintaining world-class delivery standards in digitization, technology, and operations. We’re seeking individuals with a strong customer-focused approach to data and problem-solving. We analyze data, identify trends, and craft tailored solutions for our customers. This program focuses on on-the-job learning, self-study, and technical training. If you have the qualities we need, you’re ready to embark on this journey.

Qualifications and Qualities:


  • Degree in a relevant technical field (Actuarial Science, Computer Science, Electronic Engineering, Mathematics, Applied Mathematics, Financial Mathematics, Statistics, Informatics, Information Systems)
  • Minimum of 60% average throughout the studies
  • Familiarity with SQL and relational databases, including query authoring (SQL)
  • Knowledge of architectures supporting advanced analytics and data science
  • Basic analytics skills for unstructured datasets
  • Experience using data for insights and transformation in an FMCG context
  • Ability to work with cross-functional teams in a dynamic environment
  • Passion for empirical research and solving problems with data
  • Familiarity with various machine learning techniques
  • Knowledge of classical statistics
  • Proficiency in R, R Shiny, and Python
  • Experience with data visualization tools (Power BI, D3)
  • Knowledge of large dataset extraction, including unstructured data
  • Familiarity with distributed computing tools (Apache Spark, Hive, Impala)
  • Experience in Microsoft Azure and scaling analytic products in the cloud

Key Capabilities:

  • Business Acumen
  • Data Science
  • Machine Learning
  • Programming
  • Statistical Analysis
  • Data Analytics
  • Data Expertise
  • Natural Language Processing (NLP) / Natural Language Generation (NLG)
  • Model Re-engineering
  • Model Deployment
  • Python
  • Cloud Programming
  • Data Warehousing, Data Lakes

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