Billing Analyst - Managed K8s

About Bitdeer:

Bitdeer is a world-leading technology company for Bitcoin mining and AI cloud. Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers. Apart from designing industry-leading ASIC chips and manufacturing mining rigs, the Group handles complex processes involved in computing across the value chain. This includes equipment procurement, transport logistics, datacenter design and construction, equipment management, and network and facility operations. Bitdeer also offers advanced cloud capabilities to customers with a high demand for artificial intelligence. Headquartered in Singapore, Bitdeer operates globally with a diversified 3 GW energy portfolio, and deploys Bitcoin mining and HPC datacenters in the United States, Bhutan, Norway, Canada, Malaysia, and Ethiopia.

About the role

We are seeking a Billing Analyst to own the correctness of usage-to-invoice accounting for our multi-tenant GPU cloud, sitting at the intersection of finance, product, and the AI Cloud Kubernetes engineering team. As GPU capacity scales across regions, GPU types, commitment tiers, and spot/on-demand pricing, the SKU matrix behind our billing grows more complex faster than any spreadsheet can track cleanly, and every unresolved discrepancy is a customer-facing dollar amount. This role designs and maintains the pricing models that translate raw platform usage into billable line items, reconciles metered consumption against generated billing statements to catch drift before it reaches a customer invoice, and administers GPU-fault credits — determining and applying the correct credit when GPU hardware or host failures interrupt billed usage. The work requires fluency in how usage events flow from the Kubernetes platform's metering pipeline through rating and aggregation into the ledger, without requiring the person to build that pipeline. You will work with engineering to specify metering requirements and validate outputs, with finance to define pricing and credit policy, and with product to model new SKUs as GPU offerings evolve. This is a domain-analyst role, not a software engineering role, but one where analytical rigor and fluency with usage data at scale are non-negotiable. What you will be responsible for:

Pricing Model Design

: Design and maintain pricing models across the full GPU SKU matrix — GPU type, region, commitment tier, and spot versus on-demand — ensuring every combination maps to a correct, unambiguous rate. Model new pricing structures such as tiered discounts, commitment-based rates, and burst pricing as new GPU offerings and contract types launch. Translate commercial pricing decisions from product and finance into rules the metering and billing systems can execute without ambiguity. Metering and Usage Analysis

: Analyze usage data emitted by the platform's metering pipeline — GPU-hours, node-hours, storage, network egress — to validate that recorded consumption matches actual customer activity across clusters and namespaces. Define the metering requirements engineering must capture, including granularity, tagging, and timestamps, so usage attributes correctly to the right tenant, SKU, and billing period. Flag metering coverage gaps, such as partial-hour billing or multi-GPU pod scheduling, before they surface as invoice disputes. Billing Reconciliation

: Reconcile metered usage against generated billing statements and payment records line by line, isolating drift caused by rating errors, pricing misconfigurations, timing mismatches, or metering gaps. Build and maintain reconciliation processes that catch discrepancies before invoices go out, and drive root-cause investigations with engineering when drift recurs. Maintain an auditable trail from raw usage event to final invoice line for every disputed or high-value account. GPU-Fault Credit Administration

: Administer the GPU-fault credit process end to end — determining eligibility when hardware or host failures interrupt billed usage, calculating the correct credit against the affected SKU and time window, and applying it accurately to the customer's account. Maintain clear, auditable credit policies that scale as fault volume grows, and work with infrastructure/SRE teams to obtain the incident and downtime data needed to substantiate each decision. Track credit issuance trends to surface systemic reliability issues worth escalating to engineering leadership. Cross-Functional Partnership

: Serve as the billing domain expert bridging finance, product, and the AI Cloud Kubernetes engineering team, translating commercial requirements into concrete metering and billing specifications. Review new product and pricing launches for billing readiness before go-live, confirming SKUs, metering, and credit logic are fully defined. Escalate systemic billing risks, such as undercharging or credit leakage, with data-backed analysis rather than anecdote. Process and Controls

: Build repeatable, documented processes for month-end close, invoice review, and credit issuance so billing operations scale without proportional headcount growth. Establish audit checkpoints that catch billing errors before customer-facing exposure, treating every invoicing mistake as a trust and revenue risk. Maintain pricing rules, SKU definitions, and credit policies as the documented source of truth shared by engineering and finance. How you will stand out:

Bring 3+ years of experience in billing, revenue operations, or financial analysis for a usage-based or consumption-priced product, ideally in cloud infrastructure, GPU/compute, or another metered-usage business. Demonstrate a track record of owning pricing model design and billing reconciliation for a product with a non-trivial SKU matrix. Show strong analytical fluency with usage and billing data — comfortable working directly in SQL or spreadsheets against large usage-event datasets to identify drift, audit invoices, and validate metering output, rather than relying solely on pre-built dashboards. Bring demonstrated experience reconciling metered consumption against invoices at scale, with an eye for catching subtle discrepancies before they reach customers. Have direct experience with credit, adjustment, or SLA-remediation processes in a usage-based billing context — designing or administering credit policy, calculating credit amounts against complex rate structures, and maintaining full auditability of every adjustment. Be comfortable working cross-functionally with engineering to specify metering requirements and validate that platform usage data is fit for billing purposes, without needing to write the underlying metering code yourself. Familiarity with how cloud or Kubernetes usage is measured — compute-hours, GPU-hours, node- or pod-level attribution — is a strong plus. Bring precise, structured communication and documentation habits. The pricing rules, SKU definitions, and credit policies you own must be legible to finance, product, and engineering alike, since ambiguity here becomes a customer-facing billing error. What you will experience working with us:

A culture that values authenticity and diversity of thoughts and backgrounds; An inclusive and respectable environment with open workspaces and exciting start-up spirit; Fast-growing company with the chance to network with industrial pioneers and enthusiasts; Ability to contribute directly and make an impact on the future of the digital asset industry; Involvement in new projects, developing processes/systems; Personal accountability, autonomy, fast growth, and learning opportunities; Attractive welfare benefits and developmental opportunities such as training and mentoring. --------------------------------------------------------------------

Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, colour, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.

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