## Data ScientistApplylocations: Mexico, Actual León, San Pedro Garza Garciatime type: Full timeposted on: Posted Todayjob requisition id: WD*## The RoleJoin the Connected Services Business Unit as a Data Scientist developing battery-health algorithms fed by real-time vehicle data, using state-of-the-art statistical and ML techniques.
You will also strengthen core manufacturing and quality processes using machine-level data from our plants — designing systems that monitor data streams, send signals and alerts to customers, and add ML pipelines that make existing processes smarter.Connected Services develops connected solutions to reduce or eliminate no-start failures and enable in-use data — powered by sensors, gateways, and IoT — delivered to end users via APIs, dashboards, portals, and mobile apps, targeting Heavy Duty & Auto for Fleets, Aftermarket, and OE.
## 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.
## ## What You Bring (Qualifications)Required* 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 relia

📌 Data Scientist (Sinaloa)
🏢 Clarios
📍 Sinaloa