Data Scientist at Havis

Location: Warminster, Pennsylvania
Type: Full-time
Level: mid
Posted: Jul 31, 2026

Description

The Data Scientist will build scalable analytics, machine learning, AI-enabled, and reporting solutions for Finance, Operations, IT, and other business stakeholders. The role covers data engineering, SQL and database design, ETL/ELT pipelines, dashboards, forecasting, classification, optimization, model validation, data quality, integrations, and technical guidance. It is an office-based position available in Warminster, Pennsylvania; Hilliard, Ohio; Plymouth, Michigan; Burnsville, Minnesota, and Indiana, and seeks an early-career professional with approximately 3–5 years of relevant experience.

Required Skills

SQL
Python/R
Machine learning
ETL/ELT
Power BI
Data modeling
Data validation
Forecasting
Git
CI/CD

Additional Information

Minimum Education: Bachelor’s degree in Data Science, Computer Science, Information Systems, Finance, Quantitative Methods, Statistics, Engineering, or a related discipline; equivalent education and experience may be considered.
Required Previous Experiences: At least 3 years of experience in data analysis, data science, systems analysis, business intelligence, financial analytics, or a related role.
Hands-on experience with machine learning and AI concepts, including model development, evaluation, automation, prompt-based or LLM-enabled workflows, and responsible use of AI outputs.
Experience integrating ERP, financial, operational, or other enterprise-grade systems with reporting, analytics, or data warehouse environments.
Preferred Qualifications: Experience applying machine learning and AI concepts in a business environment.
Experience with Microsoft Dynamics NAV/Business Central.
Experience with manufacturing, distribution, or inventory-related data.
Hands-on experience with Power BI, including dataset design, DAX, report development, dashboard publishing, refresh management, and performance optimization.
Familiarity with CI/CD practices for data pipelines, analytics assets, reports, or software development.
Working knowledge of Access, Oracle databases, Syspro ERP, or related enterprise applications.
Knowledge of data storage strategies, partitioning, indexing, data retention, data quality controls, and governance considerations.