Manager - Growth Strategy Analytics

Background 
Marketing science and analytics has 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 organizationin 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 as Predictive Analytics in CMI (consumer and market insights).

Responsibilities:

There is an increasing opportunity for predictive analytics, with advancements in machine learning, to improve the precision of demand forecast with reduced latency andhelp uncover foresight to identify new opportunities for growthto drive portfolio, innovation, and channel strategies in the long term. Predictive Analytics is tasked with the responsibility to be at the forefront of this revolution in developing capabilities and delivering at scale.  

Increasing the precision of demand forecast will involve accounting for a multitude of available internal and external datarepresentingdifferent aspects of demand, identification of linear as well as non-linear forces shaping consumer demand, evaluation of best means of incorporating the non-linear forces (with sparse data) in the model, apply evolutions in time-series analysis and machine learning for demand forecasting. 

Incorporating foresight capabilities for uncovering new growth opportunities will involve integrating structured and unstructured data from various sources and harnessing machine learning to uncover signals that indicate potential future opportunities.     

The role of the Growth Strategy Analytics manager is a critical role to deliver on the ambition of Unilever and CMI. 

The responsibilities will focus on:

• Build Capabilities and Tools: Lead and deliver projects that will help evolve existing tools and build new tools for use across the business. The growth Strategy analytics lead, working with other members of the predictive analytics team, CMI, and external agency partners, will disintegrate the project objectives into smaller components for experimentation, assemble a team from a pool of econometricians, data scientists, data engineers, constantly monitor the outcomes of the different steps of the experiments in an agile set-up and refine approaches to deliver a minimum viable product in the agreed timelines, guide the work of the team of external analytics partners and internal work level 1 team members. These activities will require strong technical expertise which are highlighted in detail in the skills/experience section. Building capabilities/tools will start with completing the planned developments in the present roadmap.
• Manage and Evolve capabilities/tools: Once the tools are developed and agreed to be deployed across the business, work in partnership with analytics partners or relevant internal teams to make the tools as self-service UI apps for access by the business. Once the tools are deployed, on the ongoing management of the tools and constantly challenge the analytics partners to evolve the capabilities of the tools. A core focus of the role will be to manage the existing Predictive Analytics tools in the growth strategy analytics area.
• Embed/Land capabilities in the business: Partner with thebusiness teams to embed the outcomes from the tool in business decisions and ensure the outcomes from the tool are solving the desired real-world problem. Partner with the business to extend the existing tools to new markets and categories, depending on business needs. Ensure a feedback loop with the business to constantly evolve the tools. 

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

Skills and Experience:

The skill setsrequired for the effective implementation of the vision for this role are: 

Have experience with technical aspects of some of the evolutions in advanced analytics 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: 

• Time-series analysis for demand forecast especially different ways of testing and incorporating lead-lag effects. Familiar with derivatives of ARIMA models such as state space modeling.
• Experience with delivering ‘always-on’ demand forecasting models 
• Knowledge of how to account for macro-economic adjustments required for incorporating pricing in demand projections 
• Natural Language Processing (NLP) to harness unstructured text data and include the NLP constructs in time-series models 
• Use of machine learning for decomposition in mixed models 
• Use of Bayesian models for modeling 
• Good hang of optimization algorithms such as MCMC, and Genetic Algorithms. 
• Ability to integrate data from multiple data sets using deterministic and probabilistic matching 
• Exposure to predictive models such as recommendation systems to predict the pricing of new products, based on purchase behavioral data 
• Knowledge of Python, PySpark, and R. Coding will be done by external analytics partners or internal PMRA work level 1, but this role will require some knowledge of coding to be able to guide the team on possibilities and challenges in development, refinements 
• Ability to interrogate small and big data sets residing in databases using advanced SQL skills. 
• Ability to partner with Data Architecture and Engineering to help productize Innovations. Bring a product mindset to democratizing advanced analytics work.
• Have worked hands-on in a commercial environment in the area of advanced analytics, ideally in marketing function for at least 6-8+ years. Have an interest in the evolution of marketing enabled by data and data science. 
• Have proven expertise in managing stakeholders (both commercial and technical stakeholders) and managing disparate views of different stakeholders  
• Possess business acumen and the ability to work in ambiguous ever-changing environments. 
• Enthusiastic about driving Innovation, and working in connected networks and have demonstrated evidence in this regard
• Ability to communicate technical findings in a business-friendly language
• Hungry to create something new and make a mark
• Experience in democratizing advanced analytics capabilities into tools and managing the tools on an ongoing basis.