Job Description & SummaryIn PwC Deals, we help our clients to successfully carry out a transaction, whether it is buying or selling a business or company, and creating value through their merger, acquisition, financing, divestment, and restructuring processes. We work together with our clients to develop the appropriate strategy before each operation. We also evaluate the best business strategies to follow in each case and help to implement the necessary changes to take advantage of synergies and improvements after a transaction.If you can see beyond the data and like to think independently, creatively, and freshly, then PwC Deals can offer a solid career in an area of growth where you will face all kinds of intellectual challenges and will be part of an international team formed by great specialists and consultants working together to solve the most challenging projects in the environment of mergers and acquisitions.We are looking for a Senior Data Scientist with 2-4 years of experience that will help us discover the information hidden in vast amounts of data and help our clients make smarter decisions. Your primary focus will be on collecting and processing data, applying data mining techniques, doing statistical analysis, and building high-quality analytics solutions integrated with our services.ResponsibilitiesData mining using state-of-the-art methods: clustering, classification, regression, and forecasting.Enhancing data collection procedures to include information that is relevant for building analytic systems.Extending the company's data with third-party sources of information when needed.Processing, cleansing, and verifying the integrity of data used for analysis.Doing ad-hoc analysis and presenting results in a clear manner (data visualization).Selecting features, building, and optimizing classifiers using machine learning techniques.Perform clustering, regression, and forecasting analysis.Develop GIS (Geographic Information Systems) and Text Analytics solutions.Qualifications? University Degree in STEM disciplines: Computer Science, Statistics, Mathematics, Physics, or Engineering. A Master's Degree in Data and Analytics is desirable.Experience and SkillsExperience with common data science toolkits, such as Python or R. Excellence in at least one of these is highly desirable.Excellent applied understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Random Forests.Experience required in Data Analytics and tools such as Power BI, Power Query, or Power Pivot.Good applied statistics skills, such as distributions, statistical testing, regression, etc.Proficiency in Spanish and English.Good communication skills, both written and oral.Data-oriented personality.
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