Business Analyst (Food & Beverage)

SymphonyAI

14h•Hybrid

About The Position

As a Business Analyst at SymphonyAI 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. This role is ideal for someone who enjoys ambiguity, asks tough “why” questions, and can turn complex operational realities into structured, actionable insights.

Requirements

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 business/domain problems into data science problems.
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, and showcase value to the customer.
Familiarity with agile delivery models and tools (JIRA, Confluence, etc.).
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 Haves

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.

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 customers, relating 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.