Senior Data Scientist

ENGINEERINGUK
São Paulo
BRL 120.000 - 160.000
Descrição da oferta de emprego

Job Description:

This position exists to conduct data handling and quality analyses. The seniority will be set ranging from mid-level of an associate to senior depending on the university degrees, experience of the applicant in data mining, data analyses, lead/provide tactical direction and oversight of project team's work, etc.

LexisNexis Risk Solutions is the trusted data analytics provider for organizations seeking actionable insights to manage risks and improve results. Our Risk Business Analytics family contains over 100 data scientists in a fast-paced environment. We are innovators, passionate about challenging the status quo, and improving outcomes.

Qualifications:

  • Bachelor's degree in statistics, computer science, engineering, mathematics, or actuarial science.
  • Experience in data manipulation, cleansing and use/creation of relational databases.
  • Ability to learn quickly, work with a team, and communicate effectively.
  • Advanced English and fluent in Portuguese.

Pluses:

  • Created attributes for statistical modeling.
  • Analyzed and modeled for projects in the risk/fraud fields.
  • Managed data analysis projects.
  • Worked with a programming language and system to execute parallel processes.
  • Strong oral and written communication skills, including the ability to describe technical results to non-technical audiences.

Accountabilities:

  • Works across business/teams to collect, match, and consolidate data.
  • Perform data analysis for assigned business including design and development of solutions.
  • Make process and/or system improvement recommendations to assist the business in achieving its goals and objectives.
  • Clearly summarize, document, and communicate/present analytic work and/or results to internal and external clients, and analytic and non-analytic stakeholders.
  • Create attributes, optimize code and data mine in a LexisNexis Risk Solutions programming language and system (HPCC/ECL) for clusters.
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