SymphonyAI is a global leader in AI-powered enterprise solutions, helping organizations unlock value from complex data and make smarter, faster decisions. Our IndustrialAI division focuses on accelerating autonomous plant operations by connecting people, assets, and processes using predictive and generative AI.
We serve industries including Oil & Gas, Energy, Semiconductor, Chemicals, Pharmaceuticals, Utilities, Mining & Metals, across both processes and discrete manufacturing. Our mission is simple (and hard): build world-class products with real industrial impact.
As a Business Analyst at Symphony AI Industrial, you will act as the critical bridge between customers, domain experts, product, and engineering teams. You will deeply understand industrial workflows, asset management practices, and operational challenges, and translate them into clear business requirements, functional specifications, and measurable outcomes.
You’ll work closely with data scientists and engineers to ensure that advanced AI/ML solutions are solving the right problems—and that those solutions are usable, valuable, and scalable in real-world industrial environments.
This role is ideal for someone who enjoys ambiguity, asks uncomfortable “why” questions, and can turn complex operational realities into structured, actionable insights.
Job Description
Key Responsibilities
· Partner with customers, domain experts, product managers, and engineering teams to understand industrial business problems and operational workflows.
· Translate customer needs into clear business requirements, functional specifications, user stories, and acceptance criteria.
· Support discovery and solution design for predictive maintenance, asset reliability, process optimization, and operational intelligence use cases.
· Analyze operational, maintenance, and process data to identify trends, gaps, and improvement opportunities.
· Act as the voice of the customer throughout the product and solution lifecycle.
· Collaborate with data scientists to validate assumptions, interpret model outputs, and ensure business relevance of insights.
· Support solution validation, UAT, and customer rollouts to ensure expected business outcomes are achieved. · Showcase the value of the model output and platform to customer, relate them to tangible business benefits
· Assist sales and pre-sales teams by providing domain and solution context during customer discussions, demos, and workshops.
· Contribute to best practices, documentation, and repeatable frameworks for industrial analytics and AI solutions.
Qualifications
· Bachelor's or master's degree in engineering, Industrial Engineering, Operations, Analytics, or related quantitative fields.
· 5+ years of experience as a Business Analyst, Functional Analyst, or similar role in industrial, manufacturing, energy, or asset-intensive environments.
· Strong understanding of industrial operations, asset maintenance, reliability, or process control concepts.
· Proven ability to gather, structure, and document complex business requirements, translate the business / domain problem in to a data science problem.
· Experience working with cross-functional technical teams including data scientists, software engineers, and product managers.
· Ability to interpret analytical outputs and translate them into business insights and recommendations, showcasing value to customer.
· Familiarity with agile delivery models and tools (JIRA, Confluence, similar).
· Strong communication skills—comfortable engaging with both plant-floor stakeholders and senior leadership.
· Experience working with operational data sources such as historians, CMMS, EAM, or ERP systems is a strong plus.
· Exposure to AI/ML-driven analytics, predictive maintenance, or optimization solutions is highly desirable.
· Willingness to travel as required for customer engagement.
Required F&B domain knowledge
· Production operations & unit ops: mixing/blending, pasteurization (HTST/UHT), fermentation, cooking/baking/frying, CIP/SIP, aseptic processing; utilities (steam, refrigeration/ammonia, compressed air), water/wastewater.
· Packaging & lines: fillers/cappers/labelers, conveyors, checkweighers/vision/metal/X-ray, carbonation/CO2, changeovers/SMED, giveaway control, yield/weight control, OEE/downtime/loss analysis.
· Quality & food safety: HACCP/HARPC, FSMA cGMP, GFSI (BRCGS/SQF), allergen control, sanitation/hygienic design (3-A/EHEDG), microbiology & shelf-life, SPC, traceability/lot genealogy, cold chain.
· Automation & data: PLC/SCADA/MES (ISA-95/ISA-88), historians (OSIsoft PI, Aveva/Wonderware), LIMS/QMS, ERP (e.g., SAP PP-PI), GS1/EPCIS barcoding; handling time-series, batch/contextual data.
· Reliability & sustainability: rotating equipment monitoring, CMMS/EAM, predictive maintenance, ammonia refrigeration (IIAR/PSM), energy/water intensity, heat recovery, environmental compliance.
Nice to have
· Tools/platforms: Rockwell/Siemens/Schneider PLCs, FactoryTalk/WinCC/Ignition, OSIsoft PI AF/Analytics, Aveva/Wonderware, GE Proficy, and BI tools; familiarity with OPC UA/MQTT.
· Exposure to audits/standards: BRCGS/SQF audits, FDA/USDA/FSMA compliance, 3-A/EHEDG sanitary design, GS1/EPCIS traceability, ISO 22000/9001/50001.
· Continuous improvement: Lean/Six Sigma, SMED, TPM, Kaizen, loss trees; line balancing, finite-capacity scheduling, batch genealogy and recall readiness.
· Prior plant-floor experience: commissioning/startups, changeovers, CIP validation, cross-functional RCA with operations/QA/maintenance across shifts.
About Us
What Success Looks Like
· Customers clearly understand what we are building and why.
· Engineering teams receive crisp, unambiguous requirements.
· AI solutions are grounded in real operational needs—not academic exercises.
· Business outcomes are measurable, defensible, and repeatable.