Provide technical leadership, mentorship, and industry expertise to data scientists and analytics engineers, guiding high-complexity modeling and solution design.
Lead the development of analytics product packages aligned with product roadmaps or customer contracts, ensuring the end-user experience maps to clear business use cases.
Conduct research, perform advanced statistical and ML modeling, and drive the front-end analytics user experience for customer-facing solutions.
Partner across cross-functional analytics teams—including DW engineers, ETL engineers, data science engineers, data production teams, SMEs, and customers—to architect end-to-end analytics solutions.
Evaluate and integrate emerging analytics technologies, new data sources, and modern ML/AI approaches to keep Epicor’s analytics offerings innovative and competitive.
Develop and apply advanced models and algorithms to improve operations, enhance customer outcomes, and answer complex business questions.
Mine and analyze large, complex, and unstructured datasets using sophisticated statistical methods to drive data-informed decision-making and product excellence.
Collaborate with product operations leadership to ensure high availability, performance, and reliability of analytics solutions that meet or exceed contracted service levels.

9+ years’ experience building, deploying, and supporting large-scale analytics, ML, or AI solutions.
Advanced proficiency in Python, including expertise in building ML/AI models at scale.
Experience with PyTorch, ML SDKs, and production-grade machine learning frameworks.
Strong background working with large datasets and architecting scalable data science solutions.
Advanced analytical thinking, statistical and mathematical expertise, and skill in solving highly complex technical problems.
Experience with SQL and/or Python for analytics, and exposure to database modeling and data-warehousing concepts.
Experience with front-end analytics platforms such as MicroStrategy, Power BI, or Tableau.
Experience implementing ML or data science routines in Python and/or R.

Health and Wellness: Comprehensive health and wellness benefits designed to support your overall well-being.
Internal Mobility: Opportunities for mentorship, continuing education, and focused career goal setting, with 25% of positions filled internally.
Career Development: Free LinkedIn Learning licenses for everyone, along with our Mentoring Program to boost your personal development.
Education Support: Geographically specific programs to balance the cost of education with the benefits of continued learning and personal development.
Inclusive Workplace: Collaborate with a diverse team in an inclusive, global workplace that fosters innovation and celebrates partnership.
Work-Life Balance: Policies built on mutual trust and support, encouraging time off to rest, recharge, and reconnect.
Global Mobility: Comprehensive support for international relocations and permanent residency processes.

Principal Data Scientist

Key skills