Data Science

Africa Data Science & Engineering Lead

CONTEXT:
UL is driving digital transformation deliver 4G growth. Our mission is to transform our organization to a digital first culture, delivered by a world-class data and insights team, leaping ahead of our competition in everything we do.

UL’s D&A Market teams will lead the path for UL to become data-intelligent. The team will do this by delivering advanced products at scale, enabling UL functions, UniOps and leadership teams to turn data into insights, actions and decisions at a faster pace than ever before to achieve competitive edge for UL.

Each Market team consisting of technical (data engineering and science) expertise as well as functional business insight generation expertise (e.g. Finance, CMI, CD) will work with other Market teams and the D&A Global team to ensure that insights discovered locally are joined up and enhanced with regional/globally-discovered or researched insights to enable joined-up recommendations and decisions aimed at driving incremental growth by meeting the needs of our consumers, customers and employees.

With the ULE looking to D&A Market teams to power the exponential growth of UL in an in increasingly VUCA (volatile, uncertain, complex and ambiguous) context, it is imperative that D&A Market teams are organised to be highly adaptive and flexible to demand, fast-changing priorities and emergent opportunities. To do this, it will be important for the D&A Market team to have an agile mindset, org structure and ways of working (beyond agile tools and techniques) - i.e. able to embrace uncertainty, ambiguity, and to create structure out of chaos.

There are five major themes in the Data and Analytics global strategy that will relate to the work of D&A Market teams:
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 will lead data analytics, data warehousing, research development and implementation of appropriate data systems and analytic solutions. 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:
Main accountabilities:
EXPERIENCE, QUALIFICATIONS AND QUALITIES:
Essential
- B.S. or M.S. in a relevant technical field (Operations Research, Computer Science, Statistics, Engineering, or Mathematics)
- 1-8+ years’ work experience in a data science role with significant focus on large scale and/or unstructured data
- Experience managing projects from start to finish
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
- Experience building and optimising data pipelines, architectures and datasets
- Working knowledge of architectures to support advanced analytics and data science
- Strong 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
- Experience supporting and working with cross-functional teams in a dynamic environment
- Passion for empirical research and for answering hard questions with data
- Strong communication skills, particularly the ability to communicate complex quantitative insights in a precise, and actionable manner to business leaders
- Strong track record in solving analytical problems using quantitative and machine learning approaches
- Working knowledge in common machine learning techniques such as Random Forests, Boosting, Regularized Regression, Naïve Bayes Classifiers
- Working knowledge of advanced machine learning such as Deep Neural Networks, Support v