Assistant CMI Manager - Data Scientist

Job description

JOB PURPOSE

Marketing science and analytics have a rich and productive history within Unilever. For over 30 years, the CMI Advanced Analytics Unit (AAU) has been the Global Centre of Excellence for driving the agenda throughout the company, ensuring our marketing is inspired by evidence and standard methodology. We blend a strong understanding of our data sources (which describe our consumers, brands, categories, and markets) with the technical modeling expertise to derive robust insights from these data sources, all packaged in tools and software that makes it easy and intuitive for the organization in regards to decisions.

Today, the demand for analytics to power our insight and decisions is far greater than ever before, as the range of data sources available to us grows exponentially, and the technology to make sense of it evolves daily. It is imperative to be at the forefront of this revolution, ensuring that data-driven marketing becomes second nature whilst pushing the boundaries on what is possible through new modeling methodologies and democratizing the power of analytics by building user-friendly interfaces, and simulators to ensure wider adoption by business partners across the Unilever world. In line with this vision, AAU has been renamed Predictive Marketing and Shopping Analytics (PMSA) in CMI.

  Responsibilities

Data Scientists  will be working in multi-functional project teams comprising members from external agency partners and internal advanced analytics, and business leadership teams. The role of the project teams will be to design, build and embed large-scale business-relevant tools/capabilities in the area of data-driven marketing.

The responsibilities of the Data Scientist  in the project teams will be to help:

·  Build Technical Capabilities : Explore, transform, and integrate data from disparate sources/formats to create a holistic view, harness machine learning, and AI to build predictive models to drive business outcomes, visualize and explain the model outcomes to business users intuitively, ensure the models can be easily translated by deployment teams into production-ready pipelines to run on an automated continual basis.

·  Embed and Evolve Capabilities : Support PMSA managers in embedding the outputs/outcomes from the tools with business stakeholders, train business users and the CMI community on the use of the tools, help evaluate the capabilities and outputs of analytics partners, work with analytics partners to continuously challenge and improve the current models.

 

The key to success in the role is the ability to build and democratize at-scale sophistication in predictive analytics which delivers better business outcomes.

All About You

·  Professionally qualified/relevant degree: Maths & statistics, Econometrics, Operational research, Data Science

·  2+ years in an analytics role in the commercial environment

·  Technical expertise: Have experience with the technical aspects of some of the requirements below. It is fine not to have hands-on experience with all the areas outlined below but will be good to have experience in some of these areas and interest, ability to learn quickly on the other areas required on individual projects:
- Expertise in Python, SQL, R:
1. ability to interrogate small and big data with proficient coding skills
2. knowledge (hands-on modeling and business applications) of Machine learning techniques
3. ability to design, build and manage relational database

·  Beyond data science, a good hang of statistical knowledge and optimization techniques such as Bayesian models, Agent-Based Models, Genetic Algorithms

·  Experience in  data visualization  using open-source programs such as Gephi, Python / R libraries as well as platforms such as Tableau & Power BI will be an advantage

·       Marketing & brand analytics : Domain knowledge in marketing brand measurement methodologies (e.g. marketing mix modeling, digital attribution), digital marketing campaigns, and campaign performance metrics are helpful.