Description

About Us:

LayerZero Power Systems LLC. is a globally recognized leader in providing state-of-the-art power distribution solutions for critical industries. With a strong focus on reliability, innovation, and customer satisfaction, we deliver advanced power systems products that ensure uninterrupted and dependable power supply in mission-critical environments. Our customer base is comprised of companies in the data center (our focus), financial, computer service provision, and semiconductor manufacturing sectors. LayerZero Power Systems is on a trajectory of sustained growth, with a loyal customer base of existing Fortune 100 customers and an expanding portfolio of new customers.

Position Description: Data Scientist

The Data Scientist will play a critical role in transforming how LayerZero Power Systems uses data to plan, forecast, and execute operations. This role supports the Sales, Inventory, and Operations Planning (SIOP) process through advanced analytics, data modeling, and visualization to drive alignment, improve forecast accuracy, and enable data-driven decision-making across the organization.

Additionally, this position will play a key role in supporting the company’s ERP deployment, ensuring that data structures, reporting frameworks, and analytics tools are aligned with best practices to enable scalable, real-time insights across the business.

Requirements

Primary Duties:

SIOP Analytics & Forecasting

· Develop and maintain analytical models that support demand forecasting, capacity planning, and inventory optimization.

· Analyze sales, production, and supply chain data to identify trends, risks, and opportunities.

· Partner with functional leaders to improve forecast accuracy, service levels, and operational efficiency.

Data Science & Modeling

· Build predictive and prescriptive models using advanced statistical, machine learning, or optimization techniques to support SIOP decision-making.

· Perform sensitivity analyses and scenario modeling to support long-term capacity and investment planning.

· Develop algorithms and models that provide forward-looking insight into supply-demand balance, lead times, and production throughput.

ERP Deployment & Data Integration

· Serve as a key analytics lead in the ERP/MRP system deployment and post-implementation phases.

· Ensure data accuracy, integrity, and consistency across systems through close collaboration with IT, Operations, and Supply Chain teams.

· Support design and validation of ERP data structures (e.g., BOMs, routings, inventory hierarchies) for effective reporting and planning.

· Develop reporting frameworks and KPIs to leverage ERP data for real-time operational insights.

· Drive user adoption by helping build intuitive dashboards and analytical tools that connect business needs with ERP capabilities.

Business Intelligence & Visualization

· Design and maintain interactive dashboards and reports (Power BI, Tableau, or equivalent) to track KPIs such as forecast accuracy, lead times, inventory turns, and customer fill rates.

· Translate complex data into clear insights for executive leadership and cross-functional teams.

· Automate recurring data reports and develop robust data pipelines for real-time visibility.

Continuous Improvement & Data Governance

· Partner with IT and Operations to ensure data quality, consistency, and standardization across all systems.

· Contribute to the development of a best-in-class analytics infrastructure to support the company’s growth and digital transformation.

· Identify and drive process improvement opportunities within SIOP and related business processes.

Cross-Functional Collaboration

· Support strategic initiatives in production planning, material control, and procurement through analytical insights.

· Partner with Finance and Operations to model performance scenarios and improve alignment between demand and supply.

· Communicate findings effectively to both technical and non-technical audiences.

Education:

Bachelor’s or Master’s degree in Data science, Statistics, Industrial Engineering,

Skills & Experience:

· 3–7 years of experience in analytics, business intelligence, or data science (manufacturing or supply chain preferred).

· Experience supporting or integrating with ERP systems (Epicor, SAP, Oracle, or equivalent).

· Strong proficiency in SQL and data analysis tools (Python, R, or similar).

· Experience building dashboards and data visualizations (Power BI, Tableau, or equivalent).

· Solid understanding of SIOP, MRP, and manufacturing operations processes.

· Excellent problem-solving skills and business acumen; able to link analytics to operational and financial impact.

· Strong communication and storytelling skills, with the ability to present data to executive and operational audiences.

· Analytical and detail-oriented thinker

· Curious, self-driven, and proactive in problem-solving

· Comfortable working with ambiguity in a fast-growing manufacturing environment

· Collaborative mindset with cross-functional communication strength

· Passion for data accuracy, process improvement, and continuous learning

· Excitement about building systems, data models, and insights that scale with a growing business

What We Offer:

Competitive pay with performance incentives
100% company-paid medical, dental, and vision
401(k) with company match
3 weeks PTO, 10 paid holidays, and 2 floating holidays

Why You will Love Working with Us:

Impact: Develop your skills and expertise in a rapidly growing industry, with your work directly influencing the success of mission-critical projects.
Innovation: immerse yourself in an environment that celebrates forward thinking and continuous improvement.
Collaborative spirit: Work closely with engineers, marketers, and other professionals to bring ideas to life.
Grow with us: We are committed to your personal and professional development, offering endless opportunities to improve your skills and advance your career.

At LayerZero, we are proud to be an Equal Opportunity Employer. We welcome and celebrate diversity, and we are committed to creating an inclusive environment for all employees.

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