ERLPhase Power Technologies Ltd.

Data Analyst

• Own the analytics for customer-to-customer delivery: define what metrics matter, identify bottlenecks, and present recommendations to senior leadership
• Partner with the Data Science team on geographic expansion: identify highest-potential areas for growth and build the analytical foundation for investment decisions
• Work with finance to set ramp plans, targets, and success metrics for new locations
• Analyse profitability drivers across the network to understand where expansion is working and where it isn’t
• Work across squads to understand how new services affect routing, sortation, first mile, middle mile, last mile, and marketplace
• Define KPIs for new service types where no established metrics exist
• Translate ambiguous business questions into analytical frameworks - and analytical results into clear recommendations

Senior Data Analyst – New Services, Expansion

Data Scientist

• Own the data platform roadmap: transformation, semantic layer, orchestration, and the tooling that makes the team fast
• Lead and grow a team of senior analytics engineers, setting technical standards and creating space for them to do their best work
• Partner with Engineering to define contracts and expectations for how data is produced at source
• Set the self-serve strategy: make data accessible to analysts, PMs, and operators without bottlenecking on your team
• Extend the platform for automated and AI-driven systems: Ensure data is structured for programmatic action, with an uncompromising focus on accuracy and observability so that agents act on a foundation of absolute trust.
• Own strategy for emerging data types: unstructured data, telematics, real-time signals
• Represent the platform in leadership discussions, translating technical constraints into business terms

Head of Data Platform

• Identify and quantify the biggest cost-per-parcel reduction opportunities across our operations
• Build models that make operational trade-offs explicit: cost vs. reliability, speed vs. utilisation, capacity vs. flexibility
• Shape Middle Mile network design: where vehicles go, when they arrive, and how efficiently they’re used
• Drive Sortation efficiency: workforce scheduling, throughput optimisation, and the balance between human and robotic capacity
• Line manage two Analysts: set goals, provide coaching and feedback, and support their development
• Act as a trusted advisor to the squads, shaping where analytical efforts are focused and what gets prioritised
• Represent the analytical perspective in leadership discussions, influencing decisions and driving focus

Lead Data Analyst – Middle Mile & Sortation

• Own the analytics layer that powers decisions in finance (metrics, profitability models, pricing, operational KPIs).
• Build and maintain reliable dashboards and reporting.
• Translate raw operational data into useful insights for finance.
• Work with a Senior Data Scientist to build the reporting and visibility layer on top of simulation models.
• Pull metrics from various squads and shape them into required views for finance.

Senior Data Analyst – Strategic Finance

• Lead and grow a team of data scientists across multiple domains: marketplace, courier excellence, route length estimates, finance, and telematics
• Set technical direction and quality standards, reviewing meaningful work and stepping in on high-impact problems
• Own the DS roadmap: prioritise across competing demands, make tradeoffs explicit, and keep the team focused
• Partner with Product, Engineering, and Operations to turn ambiguity into plans and plans into production
• Build the team: hire strong data scientists, run a fair performance process, and help people grow in ways that compound over time
• Raise standards across velocity, model quality, and observability. When things break or slow down, you diagnose and fix
• Shape the DS function: establish cross-team forums, ways of working, and the culture that helps the team scale

Data Science Manager

• As a Senior Data Analyst, you'll work on optimizing logistics operations
• Analyze customer delivery behaviors and preferences to optimize collection rates
• Examine delivery attempt data and interaction patterns
• Analyze how customers interact with Relay's features and run experiments to evaluate impacts
• Define key performance indicators and build dashboards
• Collaborate with data scientists, engineers, and operators
• Contribute to scoped data projects from definition to delivery

Senior Data Analyst

Engineering Manager

• As an **Engineering Manager**, you are accountable for both **leading the team and shipping outcomes**.
• Your primary focus is building a team that executes well: setting clear direction, coaching engineers and tech leads, and ensuring work moves from idea to production reliably and at pace.
• You stay close to the codebase. While this is not a full-time individual contributor role, you actively review meaningful changes, pair on complex problems, and step in on high-impact or time-sensitive work when needed.
• You understand the system deeply enough to make good technical calls, unblock the team, and raise the quality bar through example.
• You run a team that owns what it builds. That means turning ambiguity into plans, plans into delivery, and delivery into real-world impact. You work tightly with Product, Design, and Operations to make tradeoffs explicit and keep the team focused on what matters most.
• You continuously raise standards across developer velocity, code quality, observability, incident response, user analytics, and product engagement. When things break, you’re involved. When execution slows, you diagnose the root cause. When the bar needs to move, you moveit.
• You also grow the team by hiring strong engineers, giving direct and timely feedback, running a fair performance process, and helping people grow in ways that compound over time.