Job Description
For Unilever to remain competitive in the future, the business needs to continue its path to become data intelligent. The dCommerce Analytics Hub is responsible for building data, data science and analytics as a core capability to help the business become data intelligent and drive business and organization performance.The team will deliver advanced products at scale and work closely with the market teams to ensure that decisions in Unilever are augmented with insight & recommendations wherever possible.Job Description
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
Develop custom data models and algorithms to apply to data sets.
Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
Develop company A/B testing framework and test model quality.
Coordinate with different functional teams to implement models and monitor outcomes.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Requirements
We're looking for someone with 5-7 years of experience manipulating data sets and building statistical models, has a master's or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:
Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
Experience working with and creating data architectures.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Excellent written and verbal communication skills for coordinating across teams.
Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc.
Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.
Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.
Unilever is an organisation committed to equity, inclusion and diversity to drive our business results and create a better future, every day, for our diverse employees, global consumers, partners, and communities. We believe a diverse workforce allows us to match our growth ambitions and drive inclusion across the business. At Unilever we are interested in every individual bringing their Whole Self to work and this includes you! Thus if you require any support or access requirements, we encourage you to advise us at the time of your application so that we can support you through your recruitment journey.