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

We are offering a project-based opportunity for independent contributors who are curious about artificial intelligence and excited to learn how advanced AI models are built, evaluated, and improved. These opportunities may be suitable for people who are early in their academic journey, exploring potential specialties, or simply eager to engage on real-world AI development work on a flexible project-by-project basis. In this project, you will interact directly with AI systems, review model outputs, follow clear task guidelines, and contribute to the creation of high-quality training data. You may work on activities such as evaluating responses, identifying inconsistencies, providing feedback, or helping structure information so that models learn more effectively. All tasks are well-defined, and you will receive task guidance and examples to help you succeed. You should be comfortable working independently, paying close attention to detail, and communicating clearly about what you observe. A thoughtful, reflective approach—explaining your reasoning and noting uncertainties—is highly valued, as it helps improve both the models and the training process. This project is well-suited for individuals who enjoy problem-solving, learning through practice, and contributing to innovative technology. This project offers a unique opportunity to gain practical exposure to AI development without needing a technical background. During your engagement you may pick up transferable skills in critical thinking, evaluation, and structured communication while contributing to systems that are shaping the future of technology across many industries. If you’re excited to learn and interested in being part of the process that helps AI systems improve and evolve, this project provides a supportive entry point into the world of AI training and development. We offer an earnings range of $18 per hour, with the exact fees determined after verifying your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As an independent contractor you’ll supply a secure computer and high‑speed internet; company‑sponsored benefits such as health insurance and PTO do not apply. Contract Type: Freelance / Contract Workplace type: Remote Seniority level: Entry Level

Role Description We are looking for skilled professionals to contribute as S2 Annotators, responsible for producing and validating high-quality Computer-Use Agent (CUA) trajectories for developer-adjacent workflows. This includes tasks such as file operations, light scripting, API interactions, and browser automation. This role requires a strong understanding of technical workflows, attention to detail, and the ability to translate natural language instructions into precise, step-by-step executable actions that can be used to train advanced AI systems. What does day-to-day look like: - Create detailed, step-by-step positive CUA trajectories for technical tasks (e.g., file manipulation, scripting, API calls, browser-based workflows) - Break down natural language instructions into clear, verifiable actions - Validate and review trajectories for correctness, completeness, and reproducibility - Work within Linux desktop environments to execute and document workflows - Use scripting (Python/Bash) to simulate or validate task execution where required - Interact with tools and environments involving APIs, terminals, and browser automation - Collaborate with internal teams to refine task quality and annotation guidelines - Ensure consistency, accuracy, and high-quality standards across all annotations Qualifications - 2–5 years of experience in software development, technical support, or similar technical roles - Strong familiarity with Linux environments and command-line operations - Proficiency in at least one scripting language: Python or Bash - Ability to decompose complex instructions into structured, step-by-step workflows - Strong attention to detail in documenting technical processes - Exposure to LLM-based tools, AI systems, or agentic workflows - Basic understanding of APIs, file systems, and developer tooling - Familiarity with OpenClaw or similar environments/tools Requirements - Prior experience in data annotation, RLHF, or SFT labeling workflows (nice to have) - Exposure to CI/CD pipelines, REST APIs, or terminal-based automation (nice to have) - Experience working with browser automation tools or developer productivity tools (nice to have) - Background in evaluating or improving AI-generated outputs (nice to have) Benefits - Engagement type: Contractor assignment/freelancer (no medical/paid leave) - Duration: 5 weeks Evaluation Process - Resume screening - Take home assessment (60 mins)

• Design and develop ML models for high impact engineering solutions • Build, train, and optimize machine learning and deep learning models to solve complex problems • Data collection and preprocessing • Feature engineering • Model evaluation and monitoring • Deployment and integration • Research and innovation • Documentation and reporting • Uphold ethical standards and ensure compliance with regulations