Data Scientist

The Data Scientist position in the Finance department supports the development of scalable analytics, machine learning, and AI-enabled solutions designed to improve decision-making, reporting accuracy, and overall business performance.

Role Overview

Working with Finance and cross-functional partners, the Data Scientist gathers and documents requirements, builds and validates analytical and predictive models, and develops ETL/ELT pipelines to power dashboards, recurring reporting, and self-service analytics. The role also includes applying advanced statistical and machine learning techniques and translating results for both technical and non-technical audiences.

Key Responsibilities

• Partner with Finance, Operations, IT, and functional leaders to understand business objectives, document requirements, assess current-state processes, and recommend data-driven solutions that improve efficiency, accuracy, and decision-making.
• Design, develop, test, and maintain analytical models, predictive tools, reporting datasets, and AI-enabled solutions using Microsoft, SQL, Python/R, LLM, and related technologies.
• Build, maintain, and optimize ETL/ELT pipelines to ingest, cleanse, transform, and validate data from multiple internal and external sources, including structured and unstructured datasets.
• Develop dashboards, recurring reports, self-service analytics tools, and executive-level visualizations that convert complex data into clear, actionable insights.
• Apply machine learning, statistical analysis, forecasting, classification, optimization, and other advanced analytical methods to support planning, performance management, operational improvement, and strategic initiatives.
• Provide technical guidance for data and analytics initiatives, ensuring alignment with business priorities, data governance expectations, security practices, documentation standards, and scalable architecture principles.
• Support enterprise-level data workflows, system interfaces, third-party software integrations, and modernization efforts, including evaluating legacy system risks and recommending long-term improvements.
• Troubleshoot data quality, database, reporting, software, and infrastructure issues; optimize SQL query performance and data refresh processes; and escalate complex matters to vendors or internal stakeholders as needed.
• Conduct code reviews, validate analytical outputs, promote reusable development practices, and help establish standards for data definitions, model documentation, testing, version control, and deployment.
• Communicate findings, recommendations, risks, and tradeoffs clearly to technical and non-technical audiences, including practical business implications of analytical results.

Required Qualifications

• Minimum 3 years of experience in data analysis, data science, systems analysis, business intelligence, financial analytics, or a related role, with experience applying ML/AI concepts in a business environment strongly preferred.
• Bachelor’s degree in Data Science, Computer Science, Information Systems, Finance, Quantitative Methods, Statistics, Engineering, or a related discipline, or an equivalent combination of education and relevant experience.
• Strong foundation in SQL, relational databases, data warehousing, data modeling, data validation, and workflow orchestration (an assessment will be administered for this skillset).
• Demonstrated analytical and problem-solving skills, including evaluating ambiguous business issues, identifying root causes, and proposing practical technical solutions.
• Ability to collaborate with cross-functional stakeholders, end users, IT partners, and third-party vendors to deliver high-quality, sustainable analytics and system solutions.
• Strong communication skills to explain technical concepts, analytical assumptions, model outputs, and business recommendations in a clear, audience-appropriate manner.
• Strong time-management, organization, and prioritization skills, including independent work, managing multiple initiatives, and meeting deadlines in a dynamic environment.
• High attention to detail with a commitment to producing accurate, reliable, repeatable, and well-documented work.
• Working understanding of accounting and finance terminology, including bookings, shipments, sales versus revenue, COGS, OpEx, debits, credits, and related reporting concepts.
• Working knowledge of ERP transaction flows, preferably within Microsoft Dynamics NAV/Business Central; experience with manufacturing, distribution, or inventory-related data is helpful.

Technical Skills and Tools

• Technologies: SQL, Python, R, LLM, ETL, ELT, Microsoft, SQL Server, Power BI, DAX, Git, CI/CD

Technical Requirements

• Advanced proficiency with Microsoft-based data, reporting, and development technologies, including SQL Server and related database tools.
• 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.
• Strong experience with relational database design, SQL development, stored procedures, triggers, query optimization, indexing strategies, and performance tuning.
• Proficiency with at least one scripting or statistical programming language, such as Python or R, for data processing, automation, modeling, and analysis.
• Strong preference for hands-on experience with Power BI, including dataset design, DAX, report development, dashboard publishing, refresh management, and performance optimization.
• Experience with Git or other version control systems; familiarity with CI/CD practices for data pipelines, analytics assets, reports, or software development preferred.
• Working knowledge of Access, Oracle databases, Syspro ERP, or related enterprise applications preferred.
• Knowledge of data storage strategies, partitioning, indexing, data retention, data quality controls, and governance considerations is a plus.
• Ability to translate complex business requirements into scalable technical designs, data models, reports, integrations, and automation solutions.
• Experience integrating ERP, financial, operational, or other enterprise-grade systems with reporting, analytics, or data warehouse environments.
• Understanding of software security, access controls, testing practices, model validation, peer review, release management, and documentation standards.

Location and Work Environment

This is an onsite office-based role located in Warminster, PA. Regular collaboration with cross-functional business partners is required, and occasional access to manufacturing, warehouse, or production areas may be necessary. Applicable safety protocols and personal protective equipment requirements must be followed.

Additional Role Details

• Department: Finance
• Accountability: Reports to the Senior Manager, Financial Planning & Analytics
• Prepared by: Human Resources
• Approved by: Senior Manager, FP&A
• Locations available (in addition to Warminster, PA): Hilliard, OH; Plymouth, MI; Burnsville, MN