• Establish and maintain the consistency, integrity and traceability of system components – hardware, software and documents – throughout their lifecycle • Track, monitor and control updates and changes of all configuration items within the boundary of the platform to maintain and ensure a ‘source of truth’ • Create and maintain configuration baselines while ensuring all changes are documented and compliant with established policies • Continuously run audits to assess and verify the accuracy and consistency of configuration items against the established baseline • Enforce change management processes through the platform’s system change requests, application review requests and document application requests • With automation and an ‘everything as code’ mentality, help execute the Kobayashi Maru configuration management framework for 14 software product teams and thousands of users across the test, IL4 development, IL6 staging/production, and higher classification level staging/production environments.

• Frame business requirements and objectives as succinct data science problems • Extraction, cleaning and transformation of relevant data for different Integrated Customer Experience Problems for analysis, modelling and reporting • Implement and deploy robust, state-of-the-art analytics and machine learning models across the Ajua Product Stack, directly impacting merchants and enterprise customers • Work with product teams to translate product feature requirements and use cases into experiments, and lead with the design, development, analysis and reporting of results, leading to decisions that directly impact customers • Actively pursue improving data science skills, including but not limited to problem-solving, writing readable/testable/efficient code, mastering Integrated Customer Experience Data, and learning to anticipate Customer and Data related product issues and needs • Actively participate in internal Data Science and broader technology project reviews and participate in community meet-ups • Collaboratively work with the engineering, products, and customer success teams and communicate clearly and effectively regardless of seniority

• Partner closely with our clients' executive and technical teams to guide decisions relating to AI, analytics, data engineering and data in general • Proactively identify and champion projects that solve complex problems across multiple domains • Apply specialized skills and fundamental data science methods (e.g. experimental design, recommender systems and machine learning when needed) to inform improvements to clients' businesses • Design and implement end-to-end data pipelines: work closely with stakeholders to build models, tables or schemas that support business processes • Empower teams both internal and external to build and maintain actionable KPIs, production-quality dashboards, informative deep dives, and scalable data products

• Analyzing billions of blockchain wallets and tens of billions of transactions to derive actionable insights • Developing and refining both descriptive statistics and predictive models • Collaborating closely with engineers and product teams to develop models that drive data-driven decisions • Enhancing our product offerings and identifying new growth opportunities • Optimizing models for performance and cost in distributed data warehouses • Conducting data mining on public data to extract actionable insights • Managing ETL connectors to ensure seamless data flow across systems • Guiding the development of visualizations to present data findings in an intuitive and accessible manner