Tiger Analytics

Senior AI Business Process Engineer

Tiger Analytics
, Rep. DominicanaPublicado hoy
Tiempo completoRemotoSeniorBusiness-Process-Engineering

Descripción del puesto

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning and AI. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

As a Senior Business Process Engineer on the Data Solutions Team, you will be responsible for rethinking and redesigning core business processes to enable automation and AI adoption. In this role, you will combine business process expertise with technical implementation skills to model, deploy, and drive adoption of redesigned processes. You will capture current workflows, build and prioritize a backlog of improvement opportunities, and guide initiatives from concept to execution while collaborating with and influencing stakeholders. By ensuring processes are scalable, AI-ready and executable by our Process Orchestration Engine, you will help unlock the full potential of decision automation and AI agents. You will establish an ongoing feedback loop by monitoring and measuring implemented processes and adjusting as needed. This role is closely connected to our enterprise data foundation and leverages a robust semantic data model to ensure redesigned processes align with company-wide data standards and deliver maximum value. This role requires the ability to rethink processes from the ground up and the courage to propose innovative changes that challenge the status quo.

Responsibilities:

Lead process discovery and redesign workshops to analyze current state, uncover root causes, and define future-state processes optimized for AI enablement.

Design, validate, and iterate executable BPMN 2.

0 and DMN models that serve as the authoritative blueprint for implementation and system integration. Your designs will also incorporate deterministic and probabilistic decision automation and integrate AI agents to enhance business outcomes.

Provide regular reporting on progress, risks, and outcomes in an agile manner to leadership and stakeholders.

Partner with business and technical teams to ensure redesigned processes integrate seamlessly with enterprise systems and data flows and always meet compliance requirements.

Collaborate with vendors and partners to manage multiple projects in parallel, ensuring deliverables meet enterprise standards and demanding timelines.

Support and enable process ownership and governance across departments, ensuring adherence to standards, security, and PII controls.

Support the cataloging of processes as assets, building a comprehensive enterprise process landscape that informs AI and automation roadmaps.

Use process mining and analytics tools (e.g., Camunda Optimize) to measure adoption, performance, and business value realization.

Advocate for practical AI adoption by demonstrating how redesigned processes and AI agents can augment human decision-making.

Collaborate closely with the Data Solutions team to align redesigned processes with the company’s data foundation, ensuring they integrate seamlessly with the semantic data model and broader data strategy

Requirements

Bachelor’s degree in Business, Information Systems, or related field.

5+ years of experience in process engineering, BPM, or process optimization.

Deep expertise in BPMN 2.

0 and DMN modeling and process redesign.

Strong skills in stakeholder facilitation, backlog management, and progress reporting.

Experience supporting multiple concurrent projects with internal teams and external vendors.

Hands-on experience designing and deploying BPMN/DMN directly in Camunda 8 (Zeebee), serving as the source of truth for delivery.

Working knowledge of data modeling principles (dimensions/facts, star schemas, slowly changing dimensions) and ability to collaborate effectively with data engineers and analysts to specify datasets, define metrics, validate results, and