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  • Posted: May 12, 2022
    Deadline: Not specified
  • On any given day, two billion people use Unilever products to look good, feel good and get more out of life. With more than 400 brands focused on health and wellbeing, no company touches so many people’s lives in so many different ways. Our portfolio ranges from nutritionally balanced foods to indulgent ice creams, affordable soaps, luxurious shampoos...
    Read more about this company


    Senior Data Scientist


    You are a data scientist with a passion for data, data science, AI and ML, demonstrating an understanding of the advanced data science models and their application into the business. This role will focus on understanding and optimising the Unilever UKI Business, building advanced and repeatable data science models that enable the business to make better decisions, drive 4G, and gain a competitive advantage.

    Main accountabilities:

    1. Understand the business problems and how to deliver relevant insights that lead to actions
    2. Gather data and build data science and algorithmic solutions to address business problems requiring descriptive, diagnostic, predictive, and/or prescriptive analytics
    3. Create experimentation to solve complex business problems and deliver predictions on future business outcomes in a repeatable and relevant way
    4. Support product teams scaling models into low-touch solutions to provide optimal ROI from data science
    5. Work on in-market business problems coming from CCBTs, CD, Finance and CLT. Identify common themes to build repeatable models and partner with CD, CCBT, Finance leadership to support 4G growth through data and analytics, and/or advance the next phase of NRM
    6. Position analytics as a tradable “currency” with customers to gain a competitive advantage
    7. Drive new value from insights from connecting external and internal data sources
    8. Innovate new data and analytic methodologies driven by local needs which feed into I&A’s global product pipeline


    Standards of Leadership Required in This Role

    • Personal Mastery (Data-science and advanced analytics)
    • Agility
    • Passion for High Performance
    • Business Acumen

    Key Skills Required

    Professional Skills

    • Machine learning forecasting techniques Fully Operational
    • Statistical modelling Fully Operational
    • Operational research and supply chain Working Knowledge
    • Optimisation techniques and tools Fully Operational
    • Manipulating multi-source data Fully Operational
    • Python coding Fully Operational
    • Cloud architecture (preferably MS Azure) Working Knowledge
    • Simulation packages e.g., Analogic Working Knowledge
    • Distributed computing (Hadoop, Spark) Working Knowledge

    General Skills

    • Project Management Working Knowledge
    • Communication/presentation skills Working Knowledge
    • Strong communication skills and ability to work with peers and demonstrate vertical and lateral influence.
    • Limitless curiosity and imagination to create novel business solutions


    • B.S. or M.S. in a relevant technical field (Operations Research, Computer Science, Statistics, Engineering, or Mathematics)
    • 1- 4+ years’ work experience in a data science role with a significant focus on a large scale and/or unstructured data
    • Experience managing projects from start to finish
    • Passion for empirical research and for answering hard questions with data
    • Ability to apply an agile analytic approach that allows for results at varying levels of precision
    • 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 o 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 vector machines, reinforcement learning and Bayesian networks
    • Working knowledge in classical statistics (Regression, Clustering, Optimization, Time Series, Probability)
    • Deep experience in testing and measurement (A/B, multivariate, inferential measurement e.g. CausalImpact)
    • Deep experience working with and coding in R, R Shiny, Python
    • Working knowledge of data visualization concepts in reports (Power BI) and specialist tools (D3 or equivalent)
    • Knowledge of extracting and combining complex, high-volume, high-dimensionality data from multiple sources (enterprise, proprietary, IoT, public domain), including unstructured data (comment threads, audio, video)
    • Working knowledge working with large data sets, experience working with distributed computing tools a plus (Apache Spark, Hive, Impala)
    • Working knowledge working in Microsoft Azure and scaling analytic products over GPUs in the cloud

    Method of Application

    Interested and qualified? Go to Unilever on to apply

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