The Predictive Modeller / Data Scientist will apply machine learning and statistical modelling methodologies to build the predictive models on product market dynamics, population, revenue, and product launches and other market events.
Work may include, but would not be limited to: · Markov-chain models, · Regressions, · Time series analysis, · Quantitative decision analysis, and decision optimization. Responsibilities will include: Understanding of the business context of the decisions to be supported Suggesting the appropriate mathematical approach Building mathematical or statistical models using the available data Use of R to design and develop analytical models for advanced techniques such as forecasts, simulations, and optimizations Development the SW code (quality, documented, and reusable) to execute the predictive models Communication & collaboration with diverse stakeholders · Assessment of the output of analytical solution and use the data to draw conclusions, identification of options, and making recommendations. Interpreting the results and provide the advices to the business stakeholders Building and maintaining of knowledge on the data sources, the data quality and metadata Recognition of the repeatable situation and suggesting the appropriate level of automation of analytics Promotion of a culture of modelling and analytics as a differentiator and competitive advantage – an environment that places high value on embedding analytical tools within business processes, and using information to make fact-based decisions. Staying in touch with modern methodology within predictive modelling
Qualification: MSc Degree in Mathematics, Statistics, Economics, or other related field. Proficient with R or other analytical tools. Preferably experience with DataScience projects.