Data Scientist

Help turn data into meaningful insights that support product and business decisions. Work with data scientists, engineers, product teams, and subject-matter experts to explore data, develop analytical solutions, and communicate findings to stakeholders. Strengthen your technical skills while contributing to customer-facing analytics and data-driven initiatives.

Responsibilities

• Analyze structured and unstructured datasets to identify trends, answer business questions, and support data-informed decision-making.
• Develop, test, and refine statistical and analytical models with support from more experienced team members.
• Contribute to analytics capabilities aligned with product roadmaps, customer needs, and defined business use cases.
• Partner with data warehouse engineers, data engineers, product teams, subject-matter experts, and other stakeholders to develop end-to-end analytical solutions.
• Prepare, clean, transform, and validate data for analysis, modeling, reporting, and experimentation.
• Evaluate new data sources and analytical methods that may support product or business needs.
• Document analytical approaches, communicate findings, and support the deployment and ongoing improvement of data science solutions.

Requirements

• 2–4 years’ experience in data science, analytics, statistical modeling, or a related field, including relevant internships, academic projects, or applied professional experience.
• Working knowledge of Python and SQL for data analysis, data preparation, modeling, and visualization.
• Understanding of statistical methods, model evaluation, and analytical problem-solving.
• Experience working with datasets to identify patterns, test hypotheses, and communicate actionable findings.
• Familiarity with database concepts, data warehousing, or data-processing workflows.
• Strong written and verbal communication skills, with the ability to explain findings to technical and nontechnical stakeholders.
• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related field, or equivalent practical experience.

Skills

• Coursework, academic projects, certifications, or early professional experience involving artificial intelligence, machine learning, or generative AI.
• Experience using Python libraries such as pandas, NumPy, scikit-learn, or similar analytical tools.
• Exposure to AI or machine-learning tools, frameworks, application programming interfaces, or cloud-based AI services.
• Experience applying AI or machine learning to practical business, product, or customer use cases.
• Exposure to R or other data science and statistical tools.
• Experience with data-visualization or business-intelligence tools such as Power BI, Tableau, or MicroStrategy.
• Familiarity with cloud data platforms, distributed data-processing environments, or production analytics workflows.

About the Company

At Epicor, we’re a team of 5,000 professionals creating a world of better business through data, AI, and cognitive ERP. We help businesses stay future-ready by connecting people, processes, and technology. From software engineers to business development reps, the work we do matters in creating a more resilient global supply chain. We foster a proactive, proud, and partnership-driven culture.

Benefits

• Comprehensive health and wellness benefits designed to support your overall well-being.
• Opportunities for mentorship, continuing education, and focused career goal setting, with 25% of positions filled internally.
• Free LinkedIn Learning licenses for everyone, along with a Mentoring Program to boost personal development.
• 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.
• Comprehensive support for international relocations and permanent residency processes.

Pay

Range: $94,000 – $151,000 USD. The salary range provided reflects the national average for this job title. Actual compensation will vary based on experience, qualifications, and market factors relevant to the position.