Data Science Specialist

ABOUT UNILEVER:

Be part of the world’s most successful, purpose-led business. Work with brands that are well-loved around the world, that improve the lives of our consumers and the communities around us. We promote innovation, big and small, to make our business win and grow; and we believe in business as a force for good. Unleash your curiosity, challenge ideas and disrupt processes; use your energy to make this happen. Our brilliant business leaders and colleagues provide mentorship and inspiration, so you can be at your best. Every day, nine out of ten Indian households use our products to feel good, look good and get more out of life – giving us a unique opportunity to build a brighter future.

Every individual here can bring their purpose to life through their work. Join us and you’ll be surrounded by inspiring leaders and supportive peers. Among them, you’ll channel your purpose, bring fresh ideas to the table, and simply be you. As you work to make a real impact on the business and the world, we’ll work to help you become a better you.

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 organization regarding 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 CMI Predictive Analytics.

Responsibilities

• Build 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 Predictive Analytics 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. 

Skills and Experience

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

Have experience with 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, PySpark, R
• Ability to work with 3rd party / Partner APIs to extract and transform data
• Ability to Integrate and impute disparate data sets using deterministic and probabilistic modeling and data fusion methodologies.
• Knowledge of distributed processing and associated requirements for big data. The ability to manage large data sets residing in databases utilizing SQL, R, or Python and experience in cloud technology (such as Azure)
• Ability to design/build or manage relational databases
• Ability to interrogate small and big data sets residing in databases using advanced SQL skills.
• Knowledge (hands-on modeling and business applications) of Machine Learning techniques (such as gradient boosting, random forest, support vector machines, k-nn, ensemble models, neural networks, and reinforcement learning)
• Expertise in some Natural Language Processing, speech analysis, and Image analysis. Ability to work with APIs of technology partners for this analysis as well as the ability to work with open-source libraries for this analysis
• Experience with feature engineering to create the same measure in different datasets with different features
• Beyond data science, good hang of statistical and optimization techniques such as Bayesian models, Agent-Based Models, Genetic Algorithms
• Expertise in propensity models
• Experience in data visualization using open-source programs such as Gephi, Python / R libraries as well as platforms such as Power BI. Experience with building reporting dashboards will be an advantage
• Ability to build pipelines in experiments (not production and deployment ready at scale) from data ingestion to transformation to modeling to visualization in the dashboard
• Ability to partner with Data Architecture / Engineering to productize Innovations
• Have worked hands-on in a commercial environment in the area of data science, ideally in media function marketing function, or related industries. Have an interest in the evolution of marketing enabled by data and data science.
• 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
• Good Project Management skills in prioritizing multiple tasks.