• Develop predictive maintenance algorithms using machine learning techniques for time-series data. • Analyze sensor data streams to identify patterns that predict equipment failure. • Research and stay up to date with academic literature and state-of-the-art condition monitoring techniques, translating relevant advances into practical solutions. • Collaborate with engineers to improve data pipelines and enhance model accuracy. • Build scalable, real-time models for low-latency predictions. • Create diagnostic tools that enable data-driven maintenance decisions. • Work with the laboratory team to design experiments and develop failure datasets using real machinery to validate hypotheses, develop new models, and optimize existing ones. • Continuously refine models based on real-world performance, experimental results, and feedback.

• Own Analytics for the Book on Vio Domain • Be the analytics and data expert for Book on Vio (BoVio), supporting decision-making across product, commercial, and operational topics. • Partner closely with Product Managers to support the definition of OKRs, roadmaps, and priorities • Lead and mentor a small team of Product Analysts through regular coaching, feedback, and growth support • Support payment and fraud analytics, as well as some of our most exciting features like Deal Freeze and Split Booking • Collaborate with the Finance team to ensure accuracy and consistency of financial data • Work with the Customer Support team to measure performance and identify opportunities to improve operational efficiency • Support Product Managers in commercial decisions with partners like payment service providers, fraud prevention tools, and dispute resolution services • Communicate proactively and educate the rest of the company through insights & best practices • Hands-on support for one of the product teams in the domain • Work closely with one of the teams, joining their sprint rituals and stand-ups. • Perform in-depth analysis on user behaviour data to discover insights & optimise the user experience • Design, QA, analyse, and interpret A/B tests and translate results into clear, actionable insights for product and engineering stakeholders • Estimate the impact of product initiatives, supporting Product Managers in prioritising initiatives against expected impact • Define tracking and build and maintain data models and dashboards using dbt and Looker • Monitor key booking funnel metrics, proactively identify anomalies or issues, and collaborate with engineers to investigate and resolve them

• Collaborate closely with marketing and other cross-functional teams to understand campaign strategies, lifecycle efforts, product usage metrics, and translate those into actionable data insights using tools like SQL and Mode • Analyze growth funnels, campaign performance, and user cohorts to identify key acquisition and retention drivers to inform product decisions • Own attribution and cohort analyses across marketing channels to optimize user acquisition strategy • Design and evaluate A/B tests and lifecycle marketing strategies to improve user conversion and engagement • Design and maintain scalable data pipelines and structured models in the data warehouse (e.g., using SQL) to power marketing dashboards, campaign tracking, and self-serve analytics • Build pipelines for blockchain transaction, order book, and market participant data to support analysis of user behavior, product engagement, and market dynamics relevant to growth strategies • Own and evolve marketing dashboards with KPIs, data visualization with strong story telling, etc. to influence marketing and product decisions for Senior Leadership

• Define and oversee standards for data organization, labelling, and validation across multiple datasets. • Establish practical frameworks to improve consistency, accuracy, and usability of structured and semi-structured data. • Ensure datasets are reviewable, auditable, and suitable for downstream analytical or software development work. • Develop repeatable workflows for data ingestion, cleaning, documentation, and version control. • Identify appropriate tools and practices to support efficient data operations without premature complexity. • Create clear documentation that enables continuity as the team scales. • Manage and mentor a distributed, India-based team performing data preparation and technical support tasks. • Translate high-level requirements into clear, actionable work-streams. • Review outputs and provide feedback to maintain quality and consistency. • Work directly with Vulcury leadership to align data efforts with near- and medium-term development plans. • Support future engineering and analytics hires by delivering well-prepared datasets and clearly defined processes. • Contribute input to planning for subsequent phases of technical development.