Data/Operations Research Analyst
Job details
- Work type
- Remote
- Compensation
- $66,000 - $106,000/yr
- Posted
- 2 weeks ago
- Apply on
- careers-peraton.icims.com
About this role
Peraton is hiring a Data/Operations Research Analyst to embed with a program and turn disparate structured and unstructured information into decision-ready analysis. The analyst will use a customer-deployed Generative AI Platform to produce dashboards, reports, and research products, while providing feedback to improve platform workflows and capabilities.
What you'll do:
- Embed within an assigned program to develop deep customer intimacy — understanding the program’s mission, stakeholders, data landscape, decision cadences, and reporting obligations — and translate that understanding into data-driven products that drive action
- Conduct broad-based data and operations research analysis across whatever data the program generates or consumes, leveraging the customer-deployed Generative AI Platform, agentic workflows, structured retrieval, and AI-assisted analytical tools to produce timely, defensible findings
- Serve as a power user of the Generative AI Platform — deeply learning its capabilities, identifying optimal workflows, and pushing the boundaries of AI-augmented data analysis and operations research
- Acquire, profile, clean, and integrate data from disparate sources — flat files, exports, APIs, databases, knowledge bases, and unstructured content — establishing the data foundations on which downstream analysis depends
- Apply quantitative methods (descriptive statistics, trend and cohort analysis, segmentation, correlation, basic inferential techniques, and where appropriate forecasting, optimization, or simulation) to answer program and customer questions
- Conduct primary and secondary research and operations analysis — literature scans, document review, stakeholder interviews, process and workflow analysis, performance studies, market and competitor scans, policy or regulatory review — and synthesize findings into clear, well-cited products
- Synthesize information from disparate, predominantly unstructured sources (documents, email threads, meeting transcripts, customer correspondence, tickets, logs, knowledge bases, structured exports) into clear, well-sourced narratives and quantitative summaries
- Design, build, and maintain dashboards, scorecards, and recurring reports that give program leadership and the customer a single, trustworthy view of status, risk, performance, and opportunity — with the analytical depth to back every number shown
- Translate ambiguous customer questions into structured analytical plans, retrieval patterns, prompt strategies, and multi-step workflows that produce repeatable, auditable answers
- Evaluate and validate AI-generated outputs, applying analytical rigor and program-specific judgment to ensure accuracy, source traceability, and methodological soundness before any product reaches the customer
- Develop reusable analytical templates, prompt libraries, dashboard components, briefing formats, and report packages that improve speed and consistency across the program and can be lifted to other programs
- Anticipate customer information needs — surfacing emerging trends, exceptions, anomalies, and risks proactively rather than waiting to be tasked
What they're looking for:
- Minimum of 2 years with BS/BA; 0 years with MS/MA
- Bachelor's degree in Data Analytics, Statistics, Mathematics, Operations Research, Industrial Engineering, Information Systems, Business Analytics, Economics, Computer Science, Engineering, Public Policy, Social Sciences, or a related analytical/research field
- Relevant experience as a data analyst, operations research analyst, research analyst, business analyst, program analyst, customer insights analyst, performance analyst, or comparable broad-based analytical role
- Demonstrated experience producing structured analytical products from diverse data sources, including unstructured documents and correspondence, semi-structured exports, and structured databases
- Demonstrated track record building dashboards, scorecards, and recurring reports that are actively used by leadership or customer stakeholders to make decisions
- Working proficiency in SQL for data extraction and shaping, plus advanced Excel; experience with at least one BI/visualization tool (Power BI, Tableau, Plotly, Looker, or equivalent)
- Working proficiency in Python or R for data wrangling, exploratory analysis, and reporting automation (pandas, plotly/matplotlib, or equivalent)
- Solid grounding in quantitative methods — descriptive statistics, trend and segmentation analysis, basic inferential statistics, and exposure to operations research techniques (forecasting, optimization, simulation, queuing, or decision analysis) — with sound judgment about when to apply them
- Demonstrated research and analysis skills — the ability to scope a question, gather authoritative sources, evaluate credibility, synthesize across sources, and cite cleanly
- Strong critical thinking, analytical reasoning, and problem-solving skills, including the ability to assess source reliability, reconcile conflicting inputs, and quantify uncertainty
- Comfort working with disparate, messy, and predominantly unstructured data — and a demonstrated ability to impose structure on it without losing fidelity
- Strong written and verbal communication skills, including the ability to brief executive and customer audiences and to produce concise, well-organized written products
Benefits:
- Employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
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