Sr AI Data Scientist

Ford Motor Company; Naucalpan de Juárez; Presencial; MXN 600,000 - 800,000; Jornada completa

Descripción de la vacante

A leading automotive company in Naucalpan de Juárez seeks an experienced Data Analyst to develop scalable solutions for complex problems. You will apply advanced data techniques and collaborate with stakeholders to enhance smart mobility. Ideal candidates will have extensive experience in machine learning and data science, with a minimum of 5 years in relevant fields.

Formación

• Proficiency in English (written and verbal).
• At least 5+ years of professional experience in machine learning, data science, or related fields.
• Strong foundation in machine learning and deep learning with various applications.

Responsabilidades

• Apply deep learning networks and statistical techniques.
• Transform large-scale data into usable forms.
• Collaborate with stakeholders to understand business problems.

Conocimientos

Machine learning

Data mining

Statistical modeling

Deep learning

Pandas

Numpy

ScikitLearn

Pytorch

TensorFlow

Keras

Feature engineering

Model evaluation

Educación

Bachelor’s or Post-Graduate degree in relevant fields

Herramientas

Docker

Flask

FastAPI

Kafka

RabbitMQ

GCP

AWS

Azure

Descripción del empleo

At Ford Motor Company, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our plans for the future of mobility, we offer a variety of opportunities to accelerate your career and help define tomorrow’s transportation.

Creating the future of smart mobility requires the intelligent use of data, metrics, and analytics. Join our Global Data Insight & Analytics team to make an impact. We enable Ford to understand business conditions, customer needs, and the competitive landscape, helping decision-makers act meaningfully. Use your data expertise and analytical skills to drive evidence-based decision-making.

The Global Data Insights and Analytics (GDI&A) department seeks qualified individuals to develop scalable solutions for complex problems using Machine Learning, Big Data, Statistics, Econometrics, and Optimization. Our goal is to provide insights from data to support evidence-based decision making across various applications such as Connected Vehicle, Smart Mobility, Operations, Manufacturing, Supply Chain, Logistics, and Warranty Analytics.

Ideal candidates will have extensive knowledge in machine learning, data mining, and statistical modeling. You should be able to translate business problems into analytical ones, identify relevant data, select and validate appropriate algorithms, and deliver insights to stakeholders. Regularly referencing research papers and staying current with algorithms, tools, and techniques is expected. This is an individual contributor role, working in project teams of 2-3 and collaborating with business partners.

Qualifications:

• Proficiency in English (written and verbal).
• Bachelor’s or Post-Graduate degree in Computer Science, Operational Research, Statistics, Applied Mathematics, or related engineering fields.
• At least 5+ years of professional experience in machine learning, data science, or related fields.
• Experience in feature engineering, hyperparameter tuning, model evaluation, etc.
• Strong foundation in machine learning and deep learning, with experience in classification, regression, unsupervised learning, computer vision, LLMs, AI agents, time series analysis, and generative AI models.
• Experience with Pandas, Numpy, ScikitLearn, Pytorch, TensorFlow, Keras.
• (Highly Desirable) Experience with Docker, REST API frameworks like Flask or FastAPI, message brokers like Kafka or RabbitMQ, and software development best practices.
• (Highly Desirable) Familiarity with cloud platforms, especially GCP (e.g., Cloud Run, BigQuery, Cloud SQL, Pub/Sub), AWS, or Azure.

Disclaimer:

Ford is an Equal Opportunity Employer committed to diversity and does not discriminate based on race, color, sex, age, national origin, religion, sexual orientation, gender identity/expression, veteran status, or disability.

Responsibilities:

• Apply deep learning networks and statistical techniques; explore new models via research or frameworks.
• Transform large-scale data into usable forms, filter data, and cross-validate models.
• Recommend and justify algorithms for specific problems.
• Enhance deep learning networks with multi-GPU and multi-node capabilities.
• Collaborate with stakeholders to understand business problems.
• Use calculus, algebra, and other math to build reliable, scalable models.
• Automate algorithms in production, standardize processes, and document best practices.
• Create technical and non-technical reports detailing project outcomes.