Data Analyst

About the Role

Hitachi Digital Services is seeking a Data Analyst to join its Global Analytics & Decision Sciences (GADS) team. This is an entry-level opportunity for a recent graduate or someone beginning a career in data, analytics, business intelligence, or decision sciences. The role follows a hybrid work model based in Norman, Oklahoma. You will work with experienced analysts, business intelligence professionals, data scientists, and stakeholders to explore business questions, prepare and analyze data, develop reports and visualizations, and communicate findings. You will gain exposure to how analytics supports areas including Supply Chain, Finance, Sales, Product Management, and Pricing. This role is suited for individuals who enjoy problem-solving, learning innovative technologies, working with data, and understanding how analytical work can improve business decisions and processes.

Key Responsibilities

• Collaborate with business stakeholders and team members to understand business questions, document requirements, and clarify the intended outcomes of analyses or reporting requests.
• Gather, organize, clean, and validate data from multiple sources for analysis and reporting.
• Utilize tools such as SQL, Python, Microsoft Excel, Power BI, and approved AI tools to explore data, perform analysis, automate routine tasks, and develop reports or visualizations.
• Support the development and maintenance of Power BI dashboards, reports, datasets, and supporting documentation.
• Perform exploratory and descriptive analysis to identify trends, patterns, outliers, and areas for further investigation.
• Assist with defining, calculating, and validating business metrics and key performance indicators (KPIs).
• Conduct data-quality checks and help identify inconsistencies, missing information, or unexpected results.
• Communicate analytical findings through clear visualizations, concise written summaries, and presentations for business audiences.
• Support testing and validation of reports, analytical solutions, data transformations, and enhancements before release.
• Partner with experienced team members on analytics, business intelligence, data science, and process improvement projects.
• Document analytical methods, data sources, business definitions, assumptions, and recurring processes for consistency and knowledge sharing.
• Participate in team reviews, training, and working sessions to understand the organization’s data, processes, and analytical standards.
• Explore new analytical tools, techniques, and technologies, and share relevant learnings with the team.
• Manage assigned tasks responsibly, communicate progress and potential issues, and incorporate feedback.

Requirements & Tech Stack

• SQL
• Python (or R)
• Microsoft Excel
• Power BI (or Tableau)
• Approved AI tools
• Relational databases
• Cloud data platforms
• APIs
• Version-control tools such as Git
• Machine learning, predictive analytics, generative AI

Qualifications

• A recently completed or soon-to-be-completed bachelor's degree in Data Science, Business Analytics, Statistics, Mathematics, Economics, Finance, Computer Science, Information Systems, Engineering, or another quantitatively oriented field.
• Foundational experience using SQL to retrieve, combine, or analyze data (through coursework, internships, research, employment, or personal projects).
• Foundational experience with at least one analytical programming language, preferably Python or R.
• Familiarity with data visualization or business intelligence tools such as Power BI or Tableau.
• Working knowledge of Microsoft Excel, including organizing, analyzing, and summarizing data.
• Basic understanding of analytical and AI concepts (e.g., descriptive statistics, data validation, regression, classification, prompt design, model limitations, responsible AI use).
• Strong analytical thinking and problem-solving skills.
• Attention to detail and a commitment to producing accurate, consistent, and well-documented work.
• Ability to communicate clearly, ask thoughtful questions, and explain findings to both technical and nontechnical audiences.
• Ability to work collaboratively with individuals from diverse functions, backgrounds, and technical experience levels.
• Demonstrated curiosity, initiative, and willingness to learn unfamiliar business concepts, data sources, and technologies.
• Ability to organize assigned work, balance multiple priorities, and respond constructively to feedback.

Prior full-time professional analytics experience is not required. Relevant experience may include internships, cooperative education, undergraduate research, capstone projects, technical coursework, student organizations, analytics competitions, hackathons, volunteer analytics projects, or independent technical projects.