Responsibilities:
- Work with complex and voluminous data sets (internal and external data) to evaluate, recommend and support the implementation of business strategies.
- Develop of commercial and risk predictive models.
- Identify and compile data sets using a variety of tools (e.g., SQL, Python) to help predict, improve and measure the success of key outcomes.
- Be responsible for documenting data requirements, data collection, processing, cleaning and exploratory data analysis; may include the use of statistical models/algorithms and data visualization techniques.
- Possibility of specialization in the fields of marketing, risk, digital and prevention of money laundering (anti-money laundering, AML).
- Appropriately assess risk when making business decisions, demonstrating particular consideration for the company's reputation and protecting Citigroup, its clients and assets, by encouraging compliance with applicable laws, rules and regulations, adhering to policy, applying sound ethical judgment regarding personal behavior, conduct and business practices and escalating, managing and reporting control issues with transparency
Qualifications:
- 0-2 years experience using tools for statistical modeling of large data sets
- Ability to effectively use complex analytical, interpretive and problem solving techniques
- Analytical, flexible, team-oriented and has good interpersonal/communication skills
- Demonstrated influencing, facilitation and partnering skills
- Advanced Excel
- Experience in Spark,python (pandas, scikit learn)
- Intermediate-advanced English
Education:
- Bachelor’s/University degree or equivalent experience
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
Licenciatura en física, matemático, actuario, Ciencias de la Computación, Ingeniería Informática, Análisis de Datos, Sistemas de Información.
Deseable: Experiencia laboral Data Scientist Jr.
Technical Skills / Knowledge:
Experiencia implementando soluciones de alto volumen de datos.
Conocimiento en estadística y probabilidad.
Conocimiento de modelos de machine Learning.
Lenguajes de programación: SQL (1 año), Python, (2 años) java Script (1 año),
Ingles intermedio.
Data Science
Time Type:
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