Company: Gridlines Gridlines is a rapidly growing financial modelling consultancy practice. We transforming the world of financial modelling, helping our clients to make complex financial decisions quickly and with confidence. We love to work with exciting clients that are making a big impact on the world around us, helping to tackle some of the world's greatest challenges. We plan to continue our rapid expansion and are looking for the brightest and best talent to join us on this journey. Role: We are seekling an experienced model audit professional that is passionate about financial modelling and driven by growth. You will work with a team of modelling professionals to analyse and review complex financial models, ensuring they are robust and reliable.

• Working across all aspects of data from engineering to building sophisticated visualizations, machine learning models and experiments • Producing data insights reports on macro trends as well as sector trends, including but not limited to DeFi, NFT, Gaming, Metaverse, L1/L2 and Middleware etc. • Analyze and interpret large volumes of on-chain transactional and operational data (both EVM and non-EVM) using proprietary and open source data tools, platforms and analytical tool kits • Processing confidential data and information according to guidelines • Managing and designing the reporting environment, including data sources, security, and metadata • Troubleshooting the reporting database environment and reports

• Responsible for analytic data needs of the business unit • Handle complex data projects and acts as a mid-level Data Analyst • Provide advanced analytical support for business operations in all the following areas: Finances, Product Analytics, Marketing promotions • Extract, load, model, and reconcile large amounts of data across multiple system platforms and sources • Conduct thorough exploratory data analysis (EDA) to uncover actionable insights and business opportunities • Utilize statistical techniques and predictive modelling to forecast gaming trends and anticipate player preferences • Review data to determine operational impacts and needed actions; elevate issues, trends, areas for improvement and opportunities to management • Develop reports and deliverables for management • Develop data using data warehouse analytical tools viz SQL, Python and Power BI • Collaborate with data engineers to design and maintain robust data pipelines, ETL processes, and data warehousing solutions • Develop and enforce data governance policies and best practices to uphold data quality standards across the organization • Design, conduct, analyze and report on quantitative and qualitative research • Display analyses results in text and visualizations to communicate results to the customers • Ensure the integrity, accuracy, and completeness of data sources through regular data validation and cleansing procedures • Support annual and ad hoc internal and external reporting requirements and prepare briefings and reports as needed • Collaborate with cross-functional teams to understand and fulfil the business requirements

• Define the KPI framework for cloud migration (strategy → measurable outcomes), including clear definitions, owners, data sources, SLAs, and alerting thresholds. • Build and maintain dashboards and automated reports for engineering leadership, and program stakeholders. • Instrument migration processes to capture quality, reliability, and performance signals (success/failure rate, rollback rate, downtime, restore times). • Establish baseline metrics and measure delta changes against migration phases (per application, team, and workload). • Monitor cloud spend and cost KPIs; analyze metrics and recommend optimization actions. • Partner with cloud engineers to validate instrumentation, tagging, and telemetry needed to generate accurate metrics. • Implement data quality best practices for migration metrics; perform regular audits and root-cause analyses of metric anomalies. • Drive continuous improvement by proposing and tracking remediation actions; help prioritize migration work based on data. • Communicate findings and insights clearly to technical and non-technical stakeholders; produce executive summaries and deep-dive analyses as required.