Apply statistical and probabilistic knowledge to design models and analytical solutions that identify and capture value in Analytics initiatives.
Skillfully use analytics tools to build models and analytical solutions, perform data analysis, and create dashboards (Python, SQL, Power BI, Spotfire, JSON). Experience in data analysis, data preparation, and data modeling. Practical experience with artificial intelligence — defining and developing/optimizing models for predictive analytics. Ability to create data presentations with a strong conceptual command of data storytelling.

Education: Bachelor's degree in Statistics, Economics, Actuarial Science, Mathematics, Engineering, Computer Science, or related fields.
Technical knowledge and required experience: Python, SQL, Power BI, Spotfire, JSON; experience with data analysis, data preparation, and data modeling; hands-on experience in artificial intelligence — defining and developing/optimizing models for predictive analytics; ability to prepare data presentations with solid data storytelling skills.
Certification: Not required.

Health plan.
Dental plan.
Prudential insurance: employees are provided, free of charge, with life insurance, funeral assistance, and a newborn benefit/newborn welcome package, according to the insurer's specific rules.
Meal voucher or food voucher.
Transportation voucher: provided for the commute home–work–home; a monthly deduction of 6% of the salary will apply, limited to the value of the benefit (optional).
Day off: time off granted on the employee's birthday, to be taken on the birthday date and/or within the birthday month.
Payroll-deductible loan (consigned loan).
Agreements and partnerships (educational institutions, gyms, language courses, among others).
Workplace exercise/stretching sessions.

Senior Data Engineer

Key skills