Data Scientist

Hirose Electric USA•Downers Grove, IL

just now•Onsite

About The Position

This is an exciting opportunity to join Hirose, an organization that for almost a hundred years has been pioneering thousands of new connectors and defining industry standards in consumer electronics, industrial automation, high speed backbone computer infrastructure, automotive, and medical applications. A compact company of smart people, Hirose uses the talents of every employee to bring innovation to put big technology in small packages. We are seeking a highly motivated and analytically driven Data Scientist with 2–5 years of experience to support data-driven decision-making across the organization. This role is designed for an individual who operates with an entrepreneurial mindset, demonstrating curiosity, initiative, and a strong desire to learn all aspects of our business. The Data Scientist will play a key role in identifying, aggregating, and analyzing data across multiple functions—including sales, distribution, operations, marketing, and production—to provide actionable insights that drive operational excellence and support domestic and global revenue growth. This role is a critical enabler of commercial and operational strategy, directly influencing pricing decisions, inventory positioning, distributor performance, and overall business competitiveness.

Requirements

2–5 years of experience in Data Science, Data Analytics, Business Intelligence, or AI/ML roles
Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, or related field (Master’s preferred)
Strong analytical thinking with the ability to solve complex business problems using data
Excellent communication skills, with the ability to present insights to executive stakeholders
Proven ability to work independently and within cross-functional teams
Strong proficiency in Python, R, SQL, or similar programming languages
Advanced experience with Tableau, Power BI, or data visualization tools
Experience with predictive modeling, machine learning, and statistical analysis
Ability to work with large, complex, multi-source datasets
Entrepreneurial Mindset: Proactive, curious, and comfortable operating in a fast-paced, growth-oriented environment
Business Acumen: Strong understanding (or desire to learn) sales, distribution, manufacturing, and supply chain dynamics; Ability to connect data insights to measurable business outcomes
Collaboration & Global Perspective: Effective in cross-functional, cross-regional environments; Able to align diverse stakeholders around data-driven decisions
Executive Communication: Communicates complex data insights in a clear, concise, and business-relevant manner
Results Orientation: Focused on driving tangible improvements in revenue, margin, efficiency, and performance

Nice To Haves

Experience in pricing analytics, supply chain analytics, or inventory optimization is a strong plus

Responsibilities

Identify, acquire, and integrate data from multiple internal and external sources
Build and maintain structured datasets and data pipelines to support business intelligence, advanced analytics, and machine learning initiatives
Enable a unified view of performance across sales, marketing, operations, and supply chain
Analyze data across key business domains, including: Sales funnel performance, pipeline conversion, and revenue forecasting; Customer engagement, account activity, and demand trends; Distribution channel and partner performance; Marketing effectiveness and lead generation; Operations, production metrics, and lead times
Apply statistical analysis, predictive modeling, and data mining techniques to generate actionable insights
Translate complex analyses into clear recommendations that drive strategic decision-making
Develop and deploy dashboards and reporting tools to track KPIs and business performance
Leverage Tableau and data visualization best practices to deliver scalable, intuitive insights
Enable leadership and cross-functional teams to make faster, data-informed decisions
Develop data-driven pricing models and algorithms aligned with market dynamics and company value proposition
Conduct competitive analysis using quantitative frameworks to evaluate product positioning
Quantify competitive advantages across attributes such as cost, performance, reliability, and lead time
Support pricing optimization, margin expansion, and win-rate improvement initiatives
Partner cross-functionally with Sales, Marketing, Product Management, and Operations to embed analytics into pricing strategy
Analyze distributor inventory, product mix, and demand signals to optimize channel performance
Integrate internal and external datasets (pipeline activity, lead times, purchasing history)
Develop models to improve inventory optimization, forecasting accuracy, and service levels
Identify opportunities to increase inventory turns, reduce imbalances, and drive revenue growth
Partner with Sales, Marketing, Operations, Supply Chain, and Finance teams across the Americas
Collaborate with global teams (including headquarters) to align data models and reporting standards
Support development of a global analytics framework for consistent performance measurement
Identify data gaps and drive improvements in data quality, governance, and reporting processes
Contribute to initiatives that enhance scalability, automation, and analytics maturity across the organization