puestos de Python en United States

We are Daimler Financial Services Mexico, a branch of the Daimler Trucks group, and we offer financial solutions that adapt to the needs of our distributors, clients, and market.

With over 25 years in Mexico, we have focused on building an excellent reputation of service; and to achieve that, we have relied on technological innovation, digital evolution, and a customer-oriented approach.

We are committed to offering excellent financial services that give value to our trademarks, distributors, clients, collaborators, and all our community where we live and work.

Data Analyst Data Analyst


Purpose:
Translate data business needs across departments to ensure a centralize reporting. Automate reports by using data tools such as Python, SAS, R, SQL and other toys.
Collaborate closely with the IT department to ensure the development cycle.
Create data quality controls to assure the sanity of the data. Propose state-of-the-art solutions to acquire knowledge from data.

Activities:

• Translate business needs into data solutions by understanding the purpose and create the proper requirements with the IT team.

• Work closely with the IT department in the implementation of solutions, test the developments, create UAT cases and provide guidance for best practices in data development.
• Monitor all data assets and reports, guaranteeing data quality. Automate operative reports and dashboards.

• Build new reports and propose new use-cases for outperform the business.

• Propose the use of new technologies and new models by continuously learning along with the regional (USA) and central (Germany) team

Competencies

• Continuous Quality/Performance improvement
• Collaboration and Teamwork
• Creativity and Innovation
• Problem Solving and Analysis
• Gets Results

Knowledge

• Bachelor’s degree in Data Scientist, Data Engineer, Actuary, Mathematician, Computer Science, Informatics, Industrial Engineer.
• Spanish (native/bilingual).
• English (conversational).

Experience

• 2+ years working with any kind of data, transforming data, data analysis and reporting.
• At least 1 year experience in the financial/banking industry.
• It’s a plus if you’re experienced in machine learning models and neural networks.

Skills

• Strong knowledge in any data language (SQL, SAS, R, Python, C, C++ or Visual Basic).
• Microsoft Office Suite (Excel, Word, Power Point, One Drive, Teams).
• It’s preferable to know some machine learning libraries like: Sklearn, Tensorflow, PyTorch.
• It’s a plus to know data engineering tools like: Airflow, Informatica, Cloud Instances (AWS, Azure, Google Cloud).

Diversity allows us to employ people with different experiences, abilities and points of view, and that is what enhances our culture and brings us to the forefront among the top global companies.
At Daimler Financial Services, we value the diversity between our employees.

In order to enrich the culture, acknowledges the importance of including people with different points of view and lifestyles into our company. When we select our talent, we focus on abilities; we do not discriminate based on ethnicity, nationality, gender, race, age, disability, social condition, health, religion, immigrant status, opinions, sexual orientation, gender identity or gender expression, marital status, university or appearance. Diversity allows us to employ people with different experiences, abilities and points of view, and that is what enhances our culture and brings us to the forefront among the top global companies.

At Daimler Financial Services, we value the diversity between our employees.

In order to enrich the culture, acknowledges the importance of including people with different points of view and lifestyles into our company. When we select our talent, we focus on abilities; we do not discriminate based on ethnicity, nationality, gender, race, age, disability, social condition, health, religion, immigrant status, opinions, sexual orientation, gender identity or gender expression, marital status, university or appearance.

Additional Information