Clarios · 1 day ago
AI Data Scientist
Milwaukee, WI
Full-time
Hybrid
Senior Level
5+ years expClarios is a leading company in energy storage solutions, and they are seeking a skilled AI Data Scientist to design, develop, and deploy machine learning and AI solutions. The role focuses on transforming complex data into actionable intelligence and involves collaboration with various teams to ensure robust and scalable solutions.
AutomotiveEnergyEnergy StorageManufacturing
Hiring Manager
Alyssa L.
Responsibilities
Hypothesis Framing & Metric Measurement: Translate business objectives into well-defined AI problem statements with clear success metrics and decision criteria. Prioritize opportunities by ROI, feasibility, risk, and data readiness; define experimental plans and acceptance thresholds to progress solutions from concept to scaled adoption
Data Analysis & Feature Engineering: Conduct rigorous exploratory data analysis to uncover patterns, anomalies, and relationships across heterogeneous datasets. Apply advanced statistical methods and visualization to generate actionable insights; engineer high-value features (transformations, aggregations, embeddings) and perform preprocessing (normalization, encoding, outlier handling, dimensionality reduction). Establish data quality checks, schemas, and data contracts to ensure trustworthy inputs
Model Development & Iteration: Design and build models across classical ML and advanced techniques—deep learning, NLP, computer vision, time-series forecasting, anomaly detection, and optimization. Run statistically sound experiments (cross-validation, holdouts, A/B testing), perform hyperparameter tuning and model selection, and balance accuracy, latency, stability, and cost. Extend beyond prediction to prescriptive decision-making (policy, scheduling, setpoint optimization, reinforcement learning), with domain applications such as OEE improvement, predictive maintenance, production process optimization, and digital twin integration in manufacturing contexts
MLOps & Performance: Develop end-to-end pipelines for ingestion, training, validation, packaging, and deployment using CI/CD, reproducibility, and observability best practices. Implement performance and drift monitoring, automated retraining triggers, rollback strategies, and robust versioning to ensure reliability in dynamic environments. Optimize for scale, latency, and cost; support real-time inference and edge/plant-floor constraints under defined SLAs/SLOs
Collaboration & Vendor Leadership: Partner with AI Product Owners, business SMEs, IT, and operations teams to translate requirements into pragmatic, integrated solutions aligned with enterprise standards. Engage process owners to validate data sources, constraints, and hypotheses; design human-in-the-loop workflows that drive adoption and continuous feedback. Provide technical oversight of external vendors—evaluating capabilities, directing data scientists/engineers/solution architects, validating architectures and algorithms, and ensuring seamless integration, timely delivery, and measurable value. Mentor peers, set coding/modeling standards, and foster a culture of excellence
Responsible AI & Knowledge Management: Ensure data integrity, model explainability, fairness, privacy, and regulatory compliance throughout the lifecycle. Establish model risk controls; maintain documentation (model cards, data lineage, decision logs), audit trails, and objective acceptance criteria for production release. Curate reusable assets (feature catalogs, templates, code libraries) and best-practice playbooks to accelerate delivery while enforcing Responsible AI principles and rigorous quality assurance
Qualification
Required
5+ years of experience in data science and machine learning, delivering production-grade solutions in corporate or manufacturing environments
Strong proficiency in Python and common data science libraries (e.g., Pandas, NumPy, scikit-learn); experience with deep learning frameworks (TensorFlow, PyTorch) and advanced techniques (NLP, computer vision, time-series forecasting)
Hands-on experience with data preprocessing, feature engineering, and EDA for large, complex datasets
Expertise in model development, validation, and deployment, including hyperparameter tuning, optimization, and performance monitoring
Experience interacting with databases and writing SQL queries
Experience using data visualization techniques for analysis and model explanation
Familiarity with MLOps best practices—CI/CD pipelines, containerization (Docker), orchestration, model versioning, and drift monitoring
Knowledge of cloud platforms (e.g., Microsoft Azure, Snowflake) and distributed computing frameworks (e.g., Spark) for scalable AI solutions
Experience with agile methodologies and collaboration tools (e.g., JIRA, Azure DevOps), working in matrixed environments across IT, analytics, and business teams
Strong analytical and business acumen, with the ability to quantify ROI and build business cases for AI initiatives
Excellent communication and stakeholder engagement skills; able to present insights and recommendations to technical and non-technical audiences
Preferred
Knowledge of LLMs and VLMs is a strong plus
Understanding of manufacturing systems (SCADA, PLCs, MES) and the ability to integrate AI models into operational workflows is a strong plus
Willingness to travel up to 10% as needed
Benefits
Medical, dental and vision care coverage and a 401(k) savings plan with company matching – all starting on date of hire
Tuition reimbursement, perks, and discounts
Parental and caregiver leave programs
All the usual benefits such as paid time off, flexible spending, short-and long-term disability, basic life insurance, business travel insurance, Employee Assistance Program, and domestic partner benefits
Company
Clarios
Clarios is an advanced energy storage solutions that develops, manufacture and distributes a portfolio of evolving battery technologies. It is a sub-organization of Brookfield Business Partners.
10001+ employees
H1B Sponsorship
Clarios has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (14)
2024 (6)
2023 (17)
2022 (22)
2021 (11)
2020 (15)
Funding
Current Stage
Late StageTotal Funding
$750M2023-04-24Debt Financing· $750M
2019-05-01Acquired
Leadership Team
Helmut Zodl
Chief Financial Officer
E
Elizabeth Powers
Chief Human Resources Officer
Recent News
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2026-01-07
2026-01-07
Company data provided by crunchbase