Scientific Data Analyst

hace 1 día


Desde casa, Colombia STEFANINI LATAM A tiempo completo
Responsibilities and Attributes

As a Data Scientist at Stefanini LATAM, you will be responsible for analyzing large and complex datasets to identify trends, patterns, and knowledge. You will develop and implement statistical models and algorithms to solve business problems, collaborate with cross-functional teams to define project objectives and deliverables, design and conduct experiments to test hypotheses and validate models, present findings and recommendations to stakeholders in a clear and concise manner, stay up-to-date with the latest advancements in data science and machine learning, and provide guidance and mentorship to junior data scientists as needed.

Requirements and Qualifications
  • Proven experience as a Data Scientist or similar role
  • Strong programming skills in languages such as Python, R, or SQL
  • Proficiency in data visualization tools (e.g., Tableau, Power BI) and statistical software (e.g., SAS, SPSS)
  • Solid understanding of algorithms and techniques in machine learning
  • Experience with big data technologies (e.g., Hadoop, Spark) is a plus
  • Excellent analytical and problem-solving skills
  • Strong communication and presentation skills
  • Ability to work independently and collaboratively in a fast-paced environment
  • Attention to detail and commitment to delivering high-quality results
Key Characteristics
  • Simplicity: Models should be as simple as possible while still fitting the observed data
  • Explanatory: A good model should provide a clear and understandable explanation of the phenomenon or system being studied
  • Verifiable: Models should be subject to testing through experiments and observations
  • Generalizable: A model should be able to explain a wide range of data and situations
  • Falsifiable: A model should be able to be refuted or falsified
  • Parsimonious: Also known as the principle of economy, it involves choosing the simplest explanation possible without sacrificing validity
  • Consistent: A model should be coherent and not contain internal contradictions
  • Conservative: A model should not generate implausible or impossible predictions
  • Pragmatic: A model should always seek practical applicability
  • Actualizable: Models should be updated and improved as new data becomes available and new findings are discovered

At Stefanini LATAM, we believe that technology can revolutionize a company, and innovation is fundamental to driving development and competitiveness. We value new ideas and the power of an open mind, recognizing that every talent is essential to the quality of our projects and our progress. We maintain our excellence by investing in technological innovations, the best partnerships, acquisitions of companies worldwide, and the hiring of highly skilled professionals.


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