Power Systems Engineer Full Time NEW

Consultant – Transmission Planning & Interconnection Strategy

Title: Power Systems Consultant (Part-time, 10 hrs/week)                                        Compensation: $150 per hour

Objective: Encode power feasibility, timeline, and risk into Nyxium’s decision engine

About Nyxium

Nyxium is a London-based deep tech company backed by top-tier investors, building an infrastructure intelligence platform for siting and deployability decisions across data centers and energy infrastructure.

We are seeking a Senior Power Systems Consultant to strengthen our grid access predictive capability, perform technical modeling, and elevate our grid intelligence beyond basic GIS mapping. The work will be conducted over six weeks, with clear deadlines and deliverables to ensure focus and impact within Nyxium’s ecosystem.

Must-Have

• 7+ years in utility / TSO / grid planning and operation
• Direct experience with data center or large industrial loads (≥20 MW)
• Hands-on with:
• Interconnection process (queues, studies, upgrades, capacity extension)
• Substations / transmission levels (HV/MV)
• Geography: US or Europe (ideally both exposure)

Expectation

Define a rule-based system that enables Nyxium to reliably determine whether a site can obtain power, on what timeline, and what constraints may prevent it. The consultant will define the rules once, and Nyxium will apply them automatically across thousands of sites using geospatial data and scoring logic.

Scope of Work

Grid interconnection Feasibility proxies (Week 1)

You will define indicators and heuristics for grid interconnection that Nyxium can compute as proxies for interconnection feasibility. The work will begin with data centers, and the methodology will be expanded in week 4 to additional markets, including battery energy storage and renewables. These proxies will be used to evaluate whether a site can be connected to the grid. They must include indicators of what makes a site power-viable versus non-viable, integrating key constraints such as:

·      substation and transmission access proximity

·      generation and load density

·      voltage level

·      existing and historical interconnection queue

These indicators and heuristic rules will be used to construct a power readiness score, with components that reflect structurally favorable or unfavorable conditions for power supply or grid connection at specific sites, such as indicative spare capacity. They should also propose hard no-go rules that depend on the asset class, for example, “> X km from ≥132 kV → NO for ≥50 MW data centers,” as well as upgrade classes (minor works versus transmission upgrades required and/or new substation build-out). In addition, they should specify, where appropriate, the required inputs Nyxium must collect.

Timeline Model (Week 2)

On week 2, you will expand upon the first week’s methodology to translate real-world grid behavior into usable timelines. You will define:

·      Time-to-power classes for each site (e.g. T1: 0–2 yrs, T2: 2–4 yrs, T3: 4–7 yrs)

·      What conditions lead to each timeline

·      Typical envisioned upgrade pathways (e.g. transmission expansion vs new substation) and associate costs

With this work, we should be able to produce a structured mapping from site characteristics to timeline estimates. The mapping rules (if/then) may be based on factors such as voltage level, region (US/EU), upgrade class, load density, renewable and data center density, and congestion proxies. An estimate of the confidence associated with each proxy and approach must also be provided (e.g., high / medium / low), depending on data caveats and other well-justified dimensions.

Red Flags & False Positives (Week 3)

By week 3, the methodologies should be safeguarded against hidden blockers. Based on the proxy models developed, critical risk patterns and common failure cases must be well documented. You will define:

·      Indicators and heuristics that provide early signals such as “site appears viable but cannot realistically secure capacity,” or “upgrade requirements will delay the project beyond viability.”

·      A list of red flags and decision rules to detect “looks good but will fail” patterns (e.g., “near substation but no spare capacity typical in the region”), along with associated data caveats.

·      A set of systematic viability checks to be performed before recommending a site.

Battery Energy Storage System and Renewable energy Variants (Week 4)

In week 4, the models will be reused and expanded to cover battery energy storage systems and renewable energy assets. Indicators and heuristics for the co-location of data centers with these assets will also be developed. The outputs for this week will be:

·      Novel adjusted weights for:

• Grid access
• Land constraint / cooling
• Additional flags:
• interconnection value zones (e.g., high-density of negative prices, curtailment)
• co-location viability with data centers

Validation (Week 5)

You will review real site outputs from Nyxium and answer:

• Would you proceed with this site?
• What is missing or incorrect?
• What would block this project in reality?

You will receive feedback that directly improves the model, validate 15–20 real sites, and, for each, provide a score, upgrade and timeline classifications, an explanation of the decision (e.g., would you proceed? — Yes/No/Conditional, with justification), and a discrepancy report (for sites deemed infeasible, explain what could make them viable, where appropriate).

Integration Requirements

Consultant must provide:

• Rule tables (clear thresholds)
• Weightings (e.g., substation proximity = 30%, voltage = 30%, etc.)
• Decision tree (if/then logic)
• Examples (good vs bad sites)

What success looks like

By the end of week 6, the Power Readiness Score and timeline classes must be live in the product. Greater than 80% agreement between consultant judgment and the model across 10 validation sites must be demonstrated, and the decision output must be enabled as: Deployable / Conditional / Not Deployable (power-driven).

The methodology and code must be clearly documented, transparent, and reproducible, with a Python-based approach preferred and aligned with industry best practices.