
51 - 200 employees
Founded 2003
đ€ Artificial Intelligence
đą Enterprise
đ€ B2B
Artificial Intelligence âą Enterprise âą B2B
Allwyn Corporation is a US-headquartered technology consulting and services firm focused on helping organizations modernize IT and leverage data to drive operational efficiency. The company offers AI & Machine Learning, data analytics and business intelligence, enterprise applications, IT modernization, agile software delivery, low-code development, offshore delivery, and SATCOM engineering services. Allwyn positions itself as a partner for public-sector and utility leaders seeking digital transformation and cites customer success (e. g. , IBTS) for modernizing government-facing applications. Headquarters are in Herndon, VA with offices in New York and an offshore delivery center in Hyderabad, India.
đ August 6
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51 - 200 employees
Founded 2003
đ€ Artificial Intelligence
đą Enterprise
đ€ B2B
Artificial Intelligence âą Enterprise âą B2B
Allwyn Corporation is a US-headquartered technology consulting and services firm focused on helping organizations modernize IT and leverage data to drive operational efficiency. The company offers AI & Machine Learning, data analytics and business intelligence, enterprise applications, IT modernization, agile software delivery, low-code development, offshore delivery, and SATCOM engineering services. Allwyn positions itself as a partner for public-sector and utility leaders seeking digital transformation and cites customer success (e. g. , IBTS) for modernizing government-facing applications. Headquarters are in Herndon, VA with offices in New York and an offshore delivery center in Hyderabad, India.
âą Lead end-to-end process discovery, BPMN modeling, gap analysis, and redesign for asset lifecycle workflows. âą Gather, document, and validate business, functional, and data requirements for system enhancements and new capabilities. âą Translate asset operations needs into system features while ensuring compliance with financial, regulatory, and audit standards. âą Define data models, metadata needs, and integration points for analytics, predictive maintenance, anomaly detection, and AI-driven insights. âą Facilitate workshops and align business, IT, data engineering, and leadership stakeholders. âą Evaluate vendor solutions, internal prototypes, and AI models for feasibility, scalability, and business value. âą Maintain BRDs, user stories, process maps, data dictionaries, and test scenarios. âą Support UAT, training, adoption, and rollout of new processes and system capabilities. âą Apply Value Stream Mapping to identify waste, bottlenecks, and cost drivers across asset lifecycle workflows. âą Lead Business Process Re-engineering initiatives to reduce cycle times, manual handoffs, and operational risk. âą Drive process excellence, data-driven decision-making, AI-powered insights, and scalable asset management processes.
âą 10+ years of experience as a Business Analyst, BPM Analyst, or Product Analyst. âą Strong experience with Asset Management Systems, including EAM, CMMS, or ERP Asset Modules. âą Hands-on expertise in BPMN and process modeling tools such as Visio, Signavio, or ARIS. âą Solid understanding of data flows, data quality, master data, and metadata management. âą Exposure to AI/ML concepts including predictive maintenance, forecasting, anomaly detection, NLP, or automation. âą Ability to write clear user stories, acceptance criteria, and process documentation. âą Experience working with data engineering, BI teams, and cloud platforms such as Azure, AWS, or GCP. âą Strong analytical, communication, and cross-functional collaboration skills. âą Experience with AI-enabled asset management or IoT/telemetry data preferred. âą Familiarity with SQL, Power BI/Tableau, or data modeling preferred. âą Knowledge of ITIL, ISO 55000, or other asset management frameworks preferred. âą Background in automation, including RPA, workflow engines, or intelligent document processing, preferred. âą Certifications such as CBAP, PMP, Lean Six Sigma, BPM, or Data Analytics preferred.
âą Remote work arrangement âą Quarterly travel for PI meetings
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