Data Scientist Tsf

hace 2 semanas

Naucalpan, México Ford Motor Company A tiempo completo

We are seeking a highly skilled and motivated Data Scientist to join our Quality Analytics team within the Global Data Insight and Analytics (GDI&A) organization at Ford Motor Company. As a Data Scientist specializing in Time Series Forecasting and Statistical Finance Modeling, you will play a critical role in developing innovative solutions to enhance the quality analytics capabilities of our organization.
- Master's degree in Computer Science, Engineering, Data Science, Statistics, Applied Mathematics, or a related data field.
- 2+ years of hands-on experience in Python programming for data analysis and machine learning.
- 1+ years’ experience in SQL programming language and relational databases.
- 2+ years of experience with time series forecasting and statistical finance modeling.
- 2+ years of experience with both supervised and unsupervised machine learning techniquesExperience with libraries and frameworks such as Prophet, ARIMA, and GARCH.

**Disclaimer**:
Ford Motor Company is an equal opportunity employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.
- Develop and deploy models focused on time series forecasting and statistical finance to extract insights from data.
- Design and implement data preprocessing and feature engineering techniques for time series and financial modeling tasks.
- Utilize supervised and unsupervised machine learning techniques to solve complex forecasting and financial modeling problems.
- Evaluate and fine-tune models for performance optimization, accuracy, and efficiency.
- Contribute maintainable code to existing and new pipelines.
- Stay up to date with the latest advancements in time series forecasting and statistical finance modeling and contribute to the continuous improvement of our methodologies and algorithms.
- Communicate findings, insights, and recommendations to stakeholders in a clear and concise manner.

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