Data Analyst- Brazil

3 semanas atrás


São Paulo, Brasil Exadel Inc Tempo inteiro

We are seeking a highly skilled Data Scientist/Analyst to join our data team.

This role will work closely with our Business Analyst team to face our business users and gather the data requirements and perform further data analytic work to ensure accurate and consistent data from sources. This role will also involve leveraging advanced data analysis techniques and machine learning models to drive strategic decision-making and derive insights from our data.

Who we are at Exadel:

Exadel is a global software consulting and development company that partners with organizations to help them become digital leaders in their industries. We look beyond the code to understand the impact our clients want to make and help them get from ideation to development and outcomes. We accelerate the results of digital transformations through an open, collaborative approach combined with our deep experience across industries, business processes, and technologies.

Exadel Financial Services is the financial arm of our organization, specializing in banking, capital markets strategy and technology consulting. Exadel is committed to service excellence and being a great place to work.Location: RemoteQualifications:
  • Bachelor's degree in Computer Science, Software Engineering or relevant work experience.
  • Strong SQL/data skills.
  • Programming skills in Python or equivalent to implement ML.
  • Experience with financial and capital markets data.
  • Solid understanding of statistical and machine learning techniques.
  • Excellent problem solving and analytical skills.
  • Strong communication and presentation skills.
  • Ability to work independently and collaboratively in a fast-paced environment.
Nice to have:
  • Experience in big data technologies (e.g. Spark, AWS Glue, Redshift, etc.)
  • Familiar with AWS data services (e.g. S3, RDS, Redshift, Glue, etc.)
Responsibilities:
  • Data Acquisition and Cleansing – source and catalog data from multiple sources, cleanse, preprocess and validate data to ensure accuracy and consistency.
  • Data Analysis and Modelling – Employ statistical and ML techniques to extract meaningful insights from complex datasets.
  • Model Implementation and Validation – Collaborate with tech teams to deploy data feeds, models into production, ensuring scalability and reliability.
  • Data Catalog - Maintain an overall data catalog for the team.
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