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Here, you can learn new skills, apply your expertise, and solve complex problems with cutting-edge technologies and solutions. You are part of a globally diverse team that supports you, drives change, and delivers successful results consistently.
Our client, a prestigious European Institution, is looking for a Data Scientist to be present at the client offices in Seville and provide their expertise in data networks.
Responsibilities
1. Utilize R and/or Python for data mining, data cleaning, data preparation, and data transformation.
2. Apply text mining and machine learning algorithms to analyze and interpret complex data sets.
3. Develop and implement machine learning models and algorithms to solve specific business or research problems.
4. Create visualizations and reports to effectively communicate findings and insights to stakeholders.
5. Conduct research to improve and innovate data processing techniques and analytical methods.
6. Stay updated with the latest advancements in data science and machine learning.
7. Work closely with cross-functional teams to understand data requirements and deliver actionable insights.
8. Collaborate with other researchers and data scientists to share knowledge and methodologies.
9. Document methodologies, processes, and results to ensure reproducibility and knowledge transfer.
10. Maintain clear and comprehensive records of data sources, algorithms, and outcomes.
11. Implement and optimize various analytical tools and techniques as needed.
12. Experiment with and adopt new data processing languages and tools to enhance analysis capabilities.
13. Present findings in English, written and verbal, to non-technical stakeholders.
14. Utilize Spanish for communication as needed, leveraging it as an asset for the Seville-based role.
Qualifications
1. Master's degree or equivalent experience in a quantitative field (Statistics, Mathematics, Computer Science, Engineering, etc.)
2. At least 4 years of experience in quantitative analytics or data modelling.
3. At least 3 years of experience in development with R.
4. Strong knowledge of data mining, cleaning, preparation, transformation, text mining, and machine learning algorithms.
5. Familiarity with other analytical tools is an asset.
6. Experience in a research context is beneficial.
7. Fluency in English is required.
8. Proficiency in Spanish is an asset.
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