Data Science & Engineering Internship - Africa

TEAM’S RESPONSIBILITIES:

• The Unilever Africa Data and Analytics team is a multi-disciplinary team that consists of actuaries, accountants, mathematicians, data scientists, engineers, economists, statisticians and other specialists who provide unique insights and expertise to our business across the business groups. Using our diverse skill sets we create value for our business stakeholders through the development of innovative solutions using advanced analytical modelling (ML & AI), robotic process automation as well as finance, customer and marketing analytics. Our team leverages a wide range of technologies and platforms to best meet the specific needs of each of our business groups and functions. Our team is collaborative and engaging and always looking for driven and high-achieving individuals.
• This team is responsible for managing the market’s demand for data, analytics, and insights. It is also responsible for streamlining in-scope processes related to data analytics and insights generation in the market, through automating, consolidating and eliminating them where appropriate to deliver a seamless, fast insights-generation experience using tooling provided by the Global D&A team.
• MAIN JOB PURPOSE:
• Data is the backbone of our organisation, and they're the team who are driving our transformation into a future-ready data intelligent business. So, it's an especially exciting time to join this Internship programme. Fast moving consumer goods sectors (FMCG) are fast-converging sectors. And here in the data analytics segment of the organisation, we’re leading the charge - by evolving our workplaces and people to meet rapidly changing business and customer needs. There is the large incoherence in the demand for data science and engineering skills verses the supply of skills of it across the continent. As a FMCG company our competitors are no longer just other FMCG organisations, these now include Start -up’s who offer more attractive, flexible “gig” type work. The attraction and retention of data science and engineering skills is also a prevalent challenge we face. For these reasons building constant skills pipeline becomes “a must do.”
• We're set to become a 100-year-old 'start-up', as we combine our innovative agility with the benefits of our respected African heritage, clear purpose, and established brand. It's an exhilarating time to work here – and we're leading the pack by implementing real and relevant changes to meet our people, business, and customer needs. We have a very dynamic culture one with a steep initial learning curve, tailored for individuals who want to augment their data science and engineering skills with core business skills as well. We are passionate about Africa as our home and our ability and responsibility to drive her growth.
• This 24-month Internship programme offers a transformative journey – as we work to future-proof our team’s skills and capabilities, while meeting world-class delivery standards across digitisation; technology and operations in our drive to win.   We’re looking for talented individuals who have a deep customer obsession with data and solving problems and are inspired by solving real customer problems by analysing data, identifying trends and building bespoke solutions for our customers. This programme construct is bespoke and has a strong learning on the job, self-learning and technical training focus. If you have what it takes, then…you’re Good to Go.

QUALIFICATIONS AND QUALITIES:

Essential

• 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 over all years of study
• SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
• Working knowledge of architectures to support advanced analytics and data science
• Basic analytic skills related to working with unstructured datasets
• Knowledge about and experience of use of data to deliver business insights and transform delivery in an FMCG context
• Experience with building processes supporting data transformation, data structures, dependency and workload management
• A successful history of manipulating, processing and extracting value from large disconnected datasets
• Working knowledge of message queuing, stream processing, and highly scalable data stores
• Working Knowledge supporting and working with cross-functional teams in a dynamic environment
• Passion for empirical research and for answering hard questions with data
• Ability to apply an agile analytic approach that allows for results at varying levels of precision
• Strong communication skills, particularly the ability to communicate complex quantitative insights in a precise, and actionable manner to business leaders
• Basic track record in solving analytical problems using quantitative and machine learning approaches
• Knowledge in common machine learning techniques such as Random Forests, Boosting, Regularized Regression, Naïve Bayes Classifiers
• Knowledge of advanced machine learning such as Deep Neural Networks, Support vector machines, Reinforcement learning and Bayesian networks
• Knowledge in classical statistics (Regression, Clustering, Optimization, Time Series, Probability)
• Knowledge in testing and measurement (A/B, multivariate, inferential measurement e.g. Causal Impact)
• Knowledge working with and coding in R, R Shiny, Python
• Knowledge of data visualization concepts in reports (Power BI) and specialist tools (D3 or equivalent)
• Knowledge of extracting and combining complex, high-volume, high-dimensionality data from multiple sources (enterprise, proprietary, IoT, public domain), including unstructured data (comment threads, audio, video)
• Knowledge of working with large data sets, experience working with distributed computing tools a plus (Apache Spark, Hive, Impala)
• Knowledge working in Microsoft Azure and scaling analytic products over GPUs in the cloud
• Self-directed
• Possesses a natural curiosity, openness to possibilities and imagination to create novel business solutions 
• Ability to work collaboratively with peers and demonstrate vertical and lateral influence.

Professional

• Machine learning forecasting techniques                    
• Statistical modelling                                                        
• Operational research and supply chain                        
• Optimisation techniques and tools                                
• Manipulating multi-source data                                     
• Python coding                                                                    
• Cloud architecture (preferably MS Azure)                    
• Simulation packages e.g. Anylogic                                
• Distributed computing (Hadoop, Spark)                        

KEY CAPABILITIES:

• Business Acumen
• Data Science
• Machine Learning
• Programming
• Statistical Analysis
• Data Analytics
• Data Expertise
• NLP / NLG
• Model re-engineering
• Model Deployment
• Machine Learning
• Python
• Cloud programming
• Data warehouse, Data lakes