Data Scientist

hace 2 meses


Nuevo León, México Gepae A tiempo completo

Requisitos:
- Escolaridad:
- Licenciatura- Idioma:
- Inglés- Días a laborar:
- Lunes a viernes- Horario:
- 09:00:00 a 19:00:00- Área:
- Informática/ Internet/ Web- Temporalidad del puesto:
- Indefinido- Temporalidad (Meses):
- N/A- Prestaciones:
- Superiores- Prestaciones Superiores:
- Otro- Otras prestaciones superiores:
- N/A- Código vestimenta:
- Ejecutivo- Disponibilidad a rotar turno:
- No- Disponibilidad para viajar:
- No- Se requiere cambiar de residencia:
- No- Conocimientos Y Habilidades:
- English fluent
- Quantitative analytical skills
- Knowledge of appropriate industry
- Good interpersonal, negotiation and conflict resolution skills.
- Excellence in verbal and written communication forms with emphasis on persuasive communication, tact and negotiation.
- Business process knowledge of assigned area(s) and/or function(s).
- Knowledge of advanced data gathering and analysis techniques, including statistical analysis.- Competencias:
**Administración de innovaciones**: Sabe cómo poner en práctica las ideas creativas de los demás; sabe distinguir las ideas creativas y las sugerencias que darán resultado; sabe cómo manejar el proceso creativo de los demás; sabe cómo estimular la propuesta de nuevas ideas; sabe determinar el modo en que las ideas propuestas afectarán al mercado.- Zona de trabajo:
- NA- Actividades:
- Collaborates with business and analytics leaders to generate insights and answer business questions by using analytics techniques such as advanced data visualization, statistical analysis, randomized testing, predictive modeling, forecasting, optimization, and/or machine learning. Proposes innovative ways to look at problems by using these approaches on available enterprise data as well as customer third party data and information. Validates findings using experimental and iterative approaches. This level performs basic statistical analysis of low to moderately complex data from a single source, with heavy reliance on industry/standardized tools and existing models. Output is reviewed by higher-level Data Scientists or Analytics Manager for execution.



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