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Contract
Ref: #47917

Data Scientist

  • Practice Data

  • Technologies Business Intelligence Jobs and Data Recruitment

  • Location dublin, United Kingdom

  • Type Contract

  • In ARI, we are developing a planning tool to forcecast sales and margin budgets. The algorithm will take inputs such as: Passenger forecasts, historic sales, historic transactions, historic intake margin, etc. These sources will be used to review historic performance and to forecast future budgets. The process runs approx. quarterly and predicts the forecast for yearly, monthly, weekly & daily periods.
  • The purpose of this role is to develop an algorithm for this process and to liase with Retail Commercial & Finance teams to build the budget/forecast. Additional change requests may need to be developed to further optimse the solution. The data scientist will work closely with the data engineering team to ensure the process is automated and all integrations are set up so the process can run seamlessly in the future.
  • Responsible for development of a sales forecast model
  • Responsible for implementing any development enhancements required by the business
  • Streamlime and automate the overall process so it can run on a regular basis
  • Ability to extract historical sales data from source systems
  • Apply advanced analytics predictive modelling techniques to predict future sales
  • Present the results to stakeholders and incorporate feedback into future iterations
  • Establish process for business users to be able to run versions of models in the future
  • Work closely with the data engineering platforms team to make sure best practice engineering standards are applied to all advanced analytics solutions. 
  • Work on all aspects of the design, development and delivery of the forecasting models.
  • Previous experience using predictive analytics models for forecasting sales data
  • Have at least 3+ years’ experience in an analytics role, preferably dealing with large volumes of diverse data e.g. consumer, transactional or operational data.
  • Expert level of Python or R
  • Experience using SQL for data extraction and feature development. If data not available, ability to work with data engineers to produce the required data.
  • Previous forecasting experience using Python/R for analysing data and building statistical and machine learning models and algorithms.
  • Knowledge of a variety of machine learning techniques (Random forest, Decision trees, Time series forecasting, Classification, Regression, Clustering, Optimisation, etc.).
  • Strong quantitative, analytical and problem-solving skills. Attention to detail and accuracy are key.
  • Ability to work closely with business units to translate business questions and concerns into specific analytical questions that can be answered with available data using statistical and machine learning methods.
  • Excellent interpersonal skills, strong business acumen and business engagement skills with the ability to communicate and explain complex technical concepts and quantitative methods to a wide, non-technical audience.
  • Possess excellent creative thinking skills with emphasis on developing innovative solutions to solve complex problems ensuring analytics is delivered and communicated in a way that is user friendly and easy to interpret for the business.
  • Hold a relevant primary degree (preferably post-graduate qualification) in a relevant field of study – mathematics, computer science, statistics, operations research, etc.
  • Previous advanced analytics experience in retail, finance or similar sectors is an advantage.
  • Experience in financial planning and modelling
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