Data Scientist

Clarios; San Pedro Garza García; Presencial; MXN 874.737 - 1.224.632; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Sustainable work environment

Health benefits

Descripción de la vacante

Clarios, located in San Pedro Garza García, Mexico, seeks a qualified candidate who will construct data-analysis pipelines and develop predictive models for battery health. The role emphasizes collaboration across teams and requires strong expertise in machine learning and statistics.

Ideal applicants should bring over 3 years of relevant experience and a BS degree in a related field. The company aims for excellence in sustainable practices while driving technological advancements in mobility.

Formación

• 3+ years of experience or equivalent academic experience.
• Proficient with ML/statistics packages.
• Experience with data visualization.

Responsabilidades

• Build data-analysis pipelines for vehicle signals and manufacturing processes.
• Develop models for battery health assessments.
• Collaborate with diverse stakeholders to craft solutions.

Conocimientos

Statistical and ML foundations

Model development

Data storytelling

Collaboration across teams

Educación

BS in Statistics, Mathematics, Computer Science, or related field

Herramientas

Python

Power BI

SQL

Descripción del empleo

What You’ll Do (Impact Areas)

• Decode signals: build data-analysis pipelines to understand vehicle signals related to battery usage across applications, and machine signals related to battery manufacturing processes.
• Build battery-health intelligence: develop, validate, and maintain models that provide battery-health assessments to customers of our connected battery products.
• Optimize manufacturing: build and maintain models to increase production throughput, reduce scrap rates, and improve product quality.
• Collaborate & translate: work with data scientists, engineers, and business stakeholders to craft solutions, and communicate the data-driven decision process to non-technical stakeholders.
• Support broadly: provide ML and statistical solutions to other areas of the company as needed.

What Success Looks Like

• Reliable battery-health models in production, giving connected-product customers assessments they can trust.
• Measurable manufacturing gains: higher throughput, lower scrap rates, and improved product quality driven by machine-level data.
• Monitoring systems that surface meaningful signals and timely alerts to customers.
• Clear, well-communicated insights that non-technical stakeholders can act on.

Core Competencies

• Strong statistical and ML foundations: hypothesis testing, design of experiments, regression, classification, clustering, and time-series analysis.
• Hands-on model development, training, validation, and deployment.
• Data storytelling and visualization for both analysis and model explanation.
• Curiosity, creativity, and self-direction in a dynamic business environment.
• Effective collaboration across diverse, cross-functional teams.

Required

What You Bring (Qualifications)

• BS in Statistics, Mathematics, Computer Science, or a related engineering field.
• 3+ years of experience, or equivalent academic experience with a master’s/PhD program in a relevant field.
• Proficiency programming with Python, Julia, or R and ML/statistics packages such as Scikit-Learn, SciPy, Statsmodels, PyTorch, Keras.
• Experience with Power BI or Tableau.
• Good understanding of probability, statistics (hypothesis testing, design of experiments, power calculations, mixed-effect models), linear algebra, and the mathematical bases of ML methods.
• Good understanding of ML techniques for supervised/unsupervised learning, feature selection, dimensionality reduction, regression, classification, clustering, and time-series analysis.
• Experience interacting with databases and writing SQL queries.
• Experience developing, training, validating, and deploying ML/statistical models.
• Experience using data-visualization techniques for analysis and model explanation.
• Experience collaborating effectively with non-technical stakeholders; self-driven, curious, and creative.

Preferred

• Experience with different deep learning architectures and how each applies to different problems.
• Experience with big data technologies such as Databricks, Spark, Snowpark.
• Experience with cloud technologies such as Microsoft Azure or AWS.
• Experience deploying ML solutions for production (e.g., REST APIs in Azure ML, Docker, Kubernetes) in large data-science projects.
• Experience mentoring analysts and/or data scientists.
• Causal inference, probabilistic graphical models, Bayesian statistics, and probabilistic programming languages/packages (Stan, PyMC, PyStan).
• Experience in manufacturing, IoT, vehicle data, and/or battery engineering.
• Publications in peer-reviewed journals and/or conferences in statistics, mathematics, or machine learning.

About Clarios

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).

EEO and Applicant Information

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.

Equal Employment Opportunity: 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 [e-mail].

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.