Data Scientist

SUMMARY

The Data Scientist is a high-impact, strategic role responsible for identifying, developing, and deploying data-driven solutions that transform how Hercules Industries operates. This position goes beyond traditional analytics, focusing on driving measurable business value through advanced modeling, insight generation, and business integration.

Salary: $98,000 - $113,000 per year, DOE.

The Data Scientist partners with leadership across supply chain, operations, and commercial functions to uncover opportunities, challenge legacy processes, and enable a step-change in decision‑making and performance. This role contributes to both incremental optimization and breakthrough innovation that support long‑term enterprise value creation.

PURPOSE

Drive enterprise performance by translating complex business challenges into data‑driven solutions that improve decision‑making, optimize operations, and enable scalable, sustainable competitive advantage.

This role contributes to outcomes across forecasting → inventory → operations → performance by embedding analytics into core business processes and building a foundation for a modern, data‑driven organization.

ESSENTIAL DUTIES AND RESPONSIBILITIES

VALUE IDENTIFICATION & PROBLEM FRAMING

• Partner with executive and functional leaders to identify high‑impact opportunities for data‑driven transformation.
• Translate ambiguous business challenges into structured analytical problem statements.
• Quantify potential business value (inventory, service, margin, cash flow).
• Prioritize initiatives based on strategic importance and return.

Performance Expectations

• Consistently identify high‑value opportunities aligned with business priorities.
• Demonstrate strong problem‑structuring and critical thinking skills.
• Connect analytical work directly to financial and operational outcomes.

ADVANCED ANALYTICS & MODEL DEVELOPMENT

• Design, build, and deploy predictive and prescriptive models, including: demand forecasting, inventory optimization (safety stock, EOQ/MOQ, multi‑-echelon), supplier performance and lead‑time variability, operational efficiency and throughput optimization, pricing segmentation and optimization, estimating tools and economic optimization models.
• Apply statistical, machine‑learning, and optimization techniques.
• Ensure models are scalable, interpretable, and aligned with business realities.

Performance Expectations

• Develop models that are both technically sound and practically applicable.
• Balance sophistication with usability and business adoption.
• Continuously improve model performance and relevance.

DATA EXPLORATION & INSIGHT GENERATION

• Perform exploratory data analysis to identify trends, anomalies, and root causes.
• Partner with Data Engineering to ensure clean, reliable datasets.
• Identify and address data gaps and integrity issues.
• Build datasets and structures for ongoing decision‑making.

Performance Expectations

• Produce actionable insights, not just analysis.
• Improve data quality and usability over time.
• Build reusable data assets that scale across the organization.

BUSINESS INTEGRATION & DECISION ENABLEMENT

• Translate analytical outputs into clear, actionable insights.
• Embed models into business processes (SIOP, purchasing, planning, inventory).
• Drive adoption through usability and alignment with workflows.
• Support leadership decision‑making with data‑driven recommendations.

Performance Expectations

• Drive adoption of analytics into daily operations.
• Communicate insights clearly to non‑technical stakeholders.
• Ensure solutions are practical and sustainable.

TRANSFORMATION & INNOVATION

• Challenge legacy processes and identify step‑change improvements.
• Lead or support initiatives related to forecasting, inventory, service, and digital enablement.
• Contribute to building a data‑driven culture.

Performance Expectations

• Actively contribute to transformation initiatives.
• Identify opportunities for innovation and disruption.
• Build momentum for continuous improvement and change.

COMMUNICATION & INFLUENCE

• Present findings and recommendations to senior leadership.
• Communicate complex concepts in clear business terms.
• Influence cross‑functional stakeholders to adopt new approaches.

Performance Expectations

• Effectively communicate with both technical and business audiences.
• Build credibility as a trusted advisor.
• Drive alignment and action across teams.

KEY PERFORMANCE FOCUS AREAS

• Forecast accuracy and demand planning effectiveness.
• Inventory performance (turns, working capital, service levels).
• Operational efficiency and throughput improvements.
• Margin expansion and cost optimization opportunities.
• Data quality, integrity, and accessibility.
• Adoption of analytics within core business processes.

What Success Looks Like

• Measurable business impact across supply chain, operations, and commercial performance.
• Data‑driven decision‑making becomes embedded in daily operations.
• Strong adoption of models and insights across the organization.
• Continuous pipeline of high‑value analytical initiatives.
• Recognized as a key contributor to enterprise transformation.

QUALIFICATIONS

• Bachelor’s degree in data science, statistics, mathematics, engineering, economics, or related field (Master’s preferred).
• 3–7+ years of experience in data science, advanced analytics, or related field.
• Experience applying statistical modeling, machine learning, and optimization techniques.
• Experience working with large datasets and data visualization tools.
• Strong business acumen with ability to translate data into actionable insights.
• Experience in supply‑chain, operations, or manufacturing environments preferred.
• Proficiency in tools such as Python, R, SQL, and data visualization platforms.
• Strong problem‑solving and analytical thinking skills.
• Ability to manage multiple priorities in a fast‑paced environment.

Hercules Industries is an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, sex, sexual orientation, gender identity, age, status as a protected veteran, status as a qualified individual with disability, or other legally protected status.