Data Scientist

Location: Madrid, Madrid provincia

*** Mention DataYoshi when applying ***

  • Bachelors degree in Computer Science, Statistics, Information Systems, Economics, Mathematics or a related field
  • Must have two years of experience in the following skills:
o building statistical models and machine learning models using large datasets from multiple resources;
o working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models; using database technologies including SQL, R, Python, ETL, Oracle.
o Proficiency in a minimum of one statistical analysis tool/package: R, SPSS, SAS, Stata, Matlab, Python.
o High levels of integrity and discretion in handling confidential information
o Excellent written and verbal skills

Amazon’s EU HR Operations Project Management Office (PMO) is looking for a Data Scientist to be part of our Research Analytics group. As a member of the team, you will leverage established and novel data sources, quantitative and qualitative research, and machine learning techniques to deliver tools and insights that have a direct impact on Amazon’s workforce. You will be at the forefront of using data science to transform how Amazon attracts, develops, and retains the world’s best employees. You will work closely with the business and technical teams to perform compelling analysis that delivers actionable results. You will also build predictive workforce models that have a direct impact on day-to-day decision making and on HR project investments.

Responsibilities include:
  • Develop predictive models for important business- and people-centered outcomes
  • Design experiments to identify causal factors
  • Support in the development of analysis plans and implement appropriate modeling techniques to answer complex business questions
  • Interpret data and communicate complex findings to leaders in HR and across the business
  • Write research papers for internal audiences
  • Carry out analysis in collaboration with our Program Managers to support EU HR projects and initiatives
  • Participate in planning and design of research. Scope, conduct, direct, and coordinate all phases of research projects
  • Apply appropriate techniques to collect, organize, and analyze data to generate insights
  • Drive the collection and integration of new data and the refinement of existing data sources
  • Provide expert level consulting to HR and business leaders to develop appropriate reports, metrics and research
  • Master's or PhD in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field
  • Strong verbal and written communication and data presentation skills that allow you to clearly, compellingly, and effectively influence audiences internally and externally, across organization boundaries
  • Experience writing advanced SQL, data modeling, data mining (SQL, ETL, data warehousing) and using databases in a business environment with complex datasets
  • Proficiency in several techniques including but not limited to: Decision Trees, GLM, Clustering, Bayesian methods, SVM, linear/non-linear programming, Multi-level models, Random Forests, Choice Models, etc.
  • Experience with data mapping and org design for core HCM technology such as PeopleSoft, SAP or Oracle HCM
  • Commitment to rigorous testing and validation to ensure findings are consistent, accurate, and generalizable
  • Comfortable mining unstructured data, with the ability to transform data into a usable state using appropriate tools and techniques
  • Demonstrated ability to work effectively in a collaborative environment
  • Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
  • Proven analytical and quantitative ability and a passion for enabling customers to use data and metrics to back up assumptions, develop business cases, and complete root cause analyses
  • Able to source, work with, and combine disparate data sets to answer business questions.
  • Customer obsession and bias for action
  • Proven ability to influence change strategies with data. Examples where support for change occurred because of data

*** Mention DataYoshi when applying ***

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