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A global leader in battery technologies seeks a Data Scientist to join their Connected Services AIML team in Mexico. The ideal candidate will design and implement advanced algorithmic solutions for an industrial IoT platform, requiring expertise in machine learning, data pipelines, and strong leadership skills. Candidates should have 5+ years of experience and a Bachelor's degree in a relevant field. This role offers the opportunity to work on impactful projects in a collaborative environment.
We are seeking a Data Scientist with strong technical leadership skills to join our Connected Services AIML team. You will architect and implement advanced algorithmic solutions that power our industrial IoT platform and deliver high-impact, production-grade ML systems.
Design and deploy models for predictive maintenance, anomaly detection, asset optimization, and time-series forecasting.
Work with large-scale sensor data from connected devices.
Develop robust data pipelines and real-time inference systems integrated with both edge and cloud infrastructure.
Enforcing best practices in model development, testing, and deployment.
Collaborate with product managers and domain experts to ensure technical solutions align with strategic business goals.
Bachelor’s degree in Computer Science, Electrical Engineering, Statistics, or a related field.
5+ years of experience in machine learning and software engineering.
Demonstrated success leading technical teams or driving complex projects in a production environment.
Strong understanding of core ML and AI methods: supervised/unsupervised learning, classification, regression, clustering, deep learning, etc.
High proficiency in Python, ML frameworks (PyTorch, TensorFlow, Scikit-learn), SQL, and cloud platforms.
Experience working with time-series data.
Excellent communication skills and ability to work effectively in cross-functional teams.
Advanced degree in Computer Science, Electrical Engineering, Statistics, or a related field.
Experience in industrial or automotive industry
Knowledge of MLOps tools such as MLflow, Airflow, Docker, Kubernetes.
Experience with signal processing, edge computing, or physics-informed ML models.
Clarios is the global leader in advanced, low-voltage battery technologies for mobility. Our batteries and smart solutions power nearly every type of vehicle and are found in 1 of 3 cars on the road today. With around 18,000 employees in over 100 countries, we bring deep expertise to our Aftermarket and OEM partners, and reliability, safety and comfort to everyday lives. We answer to the planet with a rigorous sustainability focus – advancing best-in-class sustainability practices and advocating for them across our industry. We work to ensure 100% of our products sold are recyclable, and we recycle 8,000 batteries an hour in our network. You can find more information here (PDF).
To all recruitment agencies: Clarios does not accept unsolicited agency resumes/CVs. Please do not forward resumes/CVs to our careers email addresses, Clarios employees or any other company location. Clarios is not responsible for any fees related to unsolicited resumes/CVs.
Clarios, LLC is an equal employment opportunity and affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, protected veteran status, status as a qualified individual with a disability, or any other characteristic protected by law. For more information, please view EEO is the Law, EEO is the Law (supplement), and Pay Transparency Non-discrimination. If you are an individual with a disability and you require an accommodation during the application process, please email Special.Accommodations@Clarios.com.
A Note to Job Applicants: please be aware of scams being perpetrated through the Internet and social media platforms. Clarios will never require a job applicant to pay money as part of the application or hiring process.
* El índice de referencia salarialse calcula en base a los salarios que ofrecen los líderes de mercado en los correspondientes sectores. Su función es guiar a los miembros Prémium a la hora de evaluar las distintas ofertas disponibles y de negociar el sueldo. El índice de referencia no es el salario indicado directamente por la empresa en particular, que podría ser muy superior o inferior.