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Description:
A Junior Predictive Modeller / Junior Data Scientist who 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.
Your work may include, but would not be limited to:Markov-chain modelsRegressionsTime series analysisQuantitative decision analysis, and decision optimizationThis opportunity would make you part of the effort to build the product that supports the decision makers in general management, finance and commercial departments.
Your responsibilities will include:Understanding of the business context of the decisions to be supported at the level appropriate for junior positionBeing the part of the discussions on selection the appropriate mathematical approachBuilding mathematical or statistical models using the available dataUsing of R to design and develop analytical models for advanced techniques such as forecasts, simulations, and optimizationsDevelopment the SW code (quality, documented, and reusable) to execute the predictive modelsSupporting as a team member the communication & collaboration with diverse stakeholdersTaking part in the assessment of the output of analytical solution and drawing conclusions, identification of options, and making recommendations.Interpreting the results and suggesting the advices to the business stakeholdersBuilding and maintaining of knowledge on the data sources, the data quality and metadataRecognition of the repeatable situation and suggesting the appropriate level of automation of analyticsStaying in touch with modern methodology within predictive modellingQualifications:
Qualifications and Education Minimum Requirement:MSc Degree in Mathematics, Statistics, Economics, or other related field.Desired Experience and Skills:Passion for advanced analytics (mathematics) and applying it to predictive modelling.Desired Aspirations Towards Following Experience and Skills:The ability to formulate models, analyze them, and program and run simulations in some appropriate system (for example R).Extensive knowledge in one or more of the following areas: Mathematical analysis and modelling, probability, stochastic processes, econometrics, time series.Broad communication and interpersonal skills, including the ability to make high-level presentations for senior executives.Strong analytical and problem-solving skills and ability to work with incomplete or imperfect data, including ability to interpret and use the analytics results within the real business context.Ability to work both independently and collaboratively within a globally dispersed team.Creation of the analytical SW products of large scope where the collaboration tools and version control systems were leveraged.
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