Chief Data Intelligence Specialist

2 semanas atrás

Porto Alegre, Rio Grande do Sul, Brasil beBeeDataLeader Tempo inteiro R$15.489 - R$20.451
Lead Data Insights

This role is responsible for driving data-driven decisions through the leadership of a team that collects, analyzes and interprets large volumes of data using software programming and statistical models to detect patterns, trends, and relationships in data sets.

The ideal candidate will have expertise in designing, developing and optimizing data science processes and programs that enable faster delivery of development activities between environments.

Key responsibilities include:

  • Providing direct and ongoing leadership, updates, and coordination for teams responsible for mining data, and implementing models/predictions to uncover insights and business value.
  • Overseeing the design, development and optimization of data science processes and programs that enable faster delivery of development activities between environments.
  • Validating and approving critical KPIs, reporting frameworks, visualizations, tests, and research to drive business solutions using computational techniques and statistics.

The successful candidate will have strong leadership skills, including coaching, team building, and conflict resolution. Additionally, they will have advanced project management skills, excellent analytical and problem-solving skills, and advanced communication skills catered to a wide variety of audiences.

Recommended qualifications include a four-year or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, Data Science, or any other related discipline or commensurate work experience.

Typically, this role requires 7-10 years of job-related experience or 5-7 years of management experience, preferably in data analytics, statistical modeling, machine learning, or a related field.

Requirements

Must-haves:

  • Expertise in modern computer science including algorithms, data structures, software architecture.
  • Understanding of current machine learning algorithms, under which circumstances each is applicable and their pros and cons.
  • Able to compose new model architectures and objective functions.
  • Knowledge of data processing techniques and data preprocessing requirements for the common machine learning approaches.
  • Knowledge of data collection techniques.
  • Knowledge of data augmentation approaches and their pros and cons.
Why You'll Thrive

As a member of our team, you will have opportunities to collaborate with cross-functional groups, share your expertise, and contribute to innovative projects.

Our organization prioritizes professional growth and development, offering training programs, workshops, and mentorship opportunities to support your career advancement.

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