Naucalpan de Juarez, MEX, Mexico
10 hours ago
PD Academy: Data & Connected Vehicles Eng.

Ignite Your Career in Automotive Innovation with Ford!

Are you a passionate, recently graduated engineer eager to dive into the heart of automotive innovation? The FoM PD Academy (Product Development Academy) offers an unparalleled opportunity for aspiring engineers to accelerate their careers within the dynamic world of Ford's Product Development. This program is designed to cultivate the next generation of automotive leaders, immersing you in cutting-edge projects that drive technological advancements and innovation across various facets of vehicle development, with a strong focus on data-driven insights and connected vehicle technologies.

About the Role:

As a PD Academy Data & Connected Vehicles Engineer, you will be instrumental in harnessing the power of data to shape the future of Ford vehicles. This multifaceted role involves learning, collaborating, and applying advanced data engineering and analytics techniques to complex automotive challenges. You will work across the entire data lifecycle, from designing and building robust data pipelines, processing vast datasets (including those from connected vehicles), to developing algorithms that extract meaningful insights and contribute to innovative solutions for our products. You'll play a key role in understanding product requirements, translating them into data-driven strategies, and collaborating with engineering, quality, and commodity teams to drive informed decisions and enhance vehicle features, performance, and the overall customer experience.

Why Join the FoM PD Academy?

Accelerated Growth: This program is specifically designed to fast-track your development through hands-on projects, dedicated learning opportunities, and direct mentorship from industry experts. Impactful Work: Contribute to the development of cutting-edge automotive technologies that will shape the future of mobility and directly impact millions of customers worldwide. Innovative Environment: Work alongside world-class engineers in a collaborative, agile, and forward-thinking environment that embraces new technologies and methodologies. Real-World Experience: Apply your academic knowledge to solve complex, real-world engineering challenges from day one, gaining invaluable practical experience. Global Exposure: Be part of a global team, contributing to products that will reach customers across diverse markets. Future-Focused: Play a key role in Ford's journey towards a connected, electric, and autonomous future, leveraging data as a core asset.

Qualifications

Basic Qualifications:

Bachelor's degree (BS) in Computer Science, Systems Engineering, Computer Engineering, Electrical Engineering, or a closely related engineering or technical field. Excellent written and verbal communication skills in English, with the ability to articulate complex technical information clearly and concisely. Strong foundational knowledge of programming, with demonstrated experience in languages such as Python and SQL. Basic understanding of data architecture principles and database concepts (SQL and NoSQL). A foundational understanding of vehicle functions and a strong interest in the automotive industry. Ability to work effectively and collaboratively in a team-oriented environment.

Preferred Qualifications:

Familiarity with advanced analytics and data science concepts, including experience with machine learning (ML) driven products or projects. Experience or coursework in distributed analytical processing technologies (e.g., Spark, Hive, Hadoop). Familiarity with major cloud platforms (e.g., Google Cloud Platform (GCP), Microsoft Azure, Amazon Web Services (AWS)). Knowledge of in-vehicle signaling and communication mechanisms (e.g., CAN) and automotive network architectures. Experience with statistical analysis, A/B testing, and causal inference methodologies. Familiarity with other programming languages such as R, Java, VBA, or MATLAB. Awareness of software documentation best practices and version control systems (e.g., Git). Basic knowledge of web development concepts.

Ford Motor Company is an Equal Opportunity Employer, as we are committed with a diverse workforce, and do not discriminate against any employee or applicant
for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran and basis of disability.
 

Key Responsibilities

Data Pipeline & Software Development: Design, develop, and implement scalable software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large, disparate datasets, including those generated by connected vehicles. Data Analysis & Insight Generation: Collaborate with cross-functional teams (e.g., Quality, Commodity, Product Development) to identify key questions and issues, applying advanced analytical techniques to extract meaningful insights from complex data and metadata sources. System Design & Implementation: Contribute to the design and programming of methods, processes, and systems for consolidating and analyzing unstructured data, generating actionable insights and innovative solutions for product development. Problem Solving & Experimentation: Support data analysis and experimentation initiatives, helping to identify root causes of issues and validate solutions through data-driven approaches. Documentation & Best Practices: Create clear and comprehensive software documentation, adhere to coding standards, and contribute to best practices for data management, software development, and system integration. Collaboration & Communication: Effectively interact with diverse teams, translating complex technical findings into clear narratives and communicating results and recommendations to both technical and non-technical stakeholders. Continuous Learning: Actively engage in continuous learning and professional development, staying abreast of new technologies, methodologies, and best practices in data engineering, connected vehicle technologies, and automotive product development.
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