Battery optimisation is not a trading hire

Asset-backed and battery optimisation roles keep getting scoped as trading roles and then filled with traders who are bored within a year. The desk writes the brief in good faith: it sees intraday markets, prices, a P&L, so it writes a trading job. Twelve months later the trader is restless, the asset is being run like a book, and the search restarts with the same brief. The failure is in the scoping, and it repeats because the reasoning that produces it sounds right.

Why the work is different

A battery optimiser lives inside a stack of constraints that a trader never meets. State of charge. Cycling budgets and degradation curves. Warranty terms that price every extra cycle. Grid connection limits and the paperwork behind them. The co-ordination of ancillary commitments with wholesale positions, where an obligation accepted in the morning shapes what the battery can do that evening. The timing of that co-ordination varies by market, some ancillary products clear day-ahead and some near real time, but the shape of the problem is the same everywhere: the asset carries commitments forward, and the theoretical best trade is frequently forbidden by a constraint that is not visible on any price screen. The craft is squeezing value out of an asset with a memory, where every action today changes what is possible tomorrow.

Trading selects and shapes people for a different game: positions that close, days that end, a score that resets each morning. The psychological reward structure of trading, the clean feedback loop between decision and outcome, is precisely what the battery takes away. An optimiser's good decision may show up as value preserved across a warranty term, not money made by Friday. Put a good trader inside a cycling budget and the parts of the job they loved are missing. That is why they leave. And the ones who stay often run the asset the way they would trade a book, cycling hard into every spread, which the degradation curve records quietly and the warranty eventually notices loudly.

None of this makes optimisation lesser. The problem is at least as hard as trading, arguably harder: it is constrained optimisation under uncertainty with physical consequences, and the revenue stack it manages, wholesale, balancing, ancillary, keeps adding layers as markets evolve. It is simply a different problem, and different problems are solved by different people.

Who is actually good at it

The people who excel mostly came from somewhere else: energy systems engineering, dispatch desks and control rooms, VPP operations, industrial process optimisation, the quantitative end of renewables forecasting, and occasionally academia, usually its control and optimisation end, someone whose doctorate priced storage under uncertainty years before any market paid for it. Their common property is comfort with physical systems and constraints, an instinct for what the asset can actually do as opposed to what the price says it should do. Many have never held a trading title. Some have never worked at a firm with a trading floor.

Which means a search that screens for trading titles excludes the best of the pool before the first call. This is the register's general finding in miniature: most of this market's talent arrived from outside it, and battery optimisation is the role family where that is most true. The realistic candidate map for an optimisation brief covers utilities, asset owners, optimiser platforms, engineering firms and the academic corner just described, and a desk that only reads rival trading floors is searching the shallowest corner of its own pool.

There is also a segment distinction inside the pool that briefs routinely miss. Optimising a single owned battery, optimising a portfolio of tolled assets for third parties, and optimising a VPP of small distributed units are related but distinct jobs, with different tempos, different customer pressures and different tolerances for manual intervention. Someone brilliant in one segment may transfer badly to another, not for lack of ability but because the operating rhythm is different. The brief should say which of these the seat actually is.

Scoping the role correctly

Getting the scope right changes everything downstream.

The title stops pretending. "Trader" attracts traders and repels the engineers who would thrive. "Optimiser", "asset trading" or an engineering-flavoured title reads correctly to the right pool. The register can say which words each segment uses for itself because it records every title even though it classifies nobody by one: looking past the titles is the method, and the titles left behind are a map of the market's own vocabulary.

The interview changes hands. A trading interview tests market views and risk appetite. An optimisation interview should test the constraint stack: walk me through a day where the afternoon forecast broke; what does your dispatch logic do when ancillary and wholesale conflict; how do you price a cycle. The best interviewers for this are the desk's own engineers and quants alongside the head of trading, not the trading floor alone.

The benchmark moves. Optimisation compensation does not track trading compensation, it has its own market, shaped by asset owners and platforms as much as by trading firms. Benchmarking an optimiser against trader pay either overpays the seat or, more often, builds in a resentment that surfaces at the first bonus round when the optimiser discovers what the traders made.

And the pitch inverts. The story that lands with this pool is the asset and the problem: real hardware, real constraints, a control problem with a price attached, and the data to work with. The trading floor, the pitch that desks reach for by default, is for many of these candidates a mild deterrent, associated with noise, ego and a culture they deliberately did not join. The strongest recruiting sentence for an optimiser is a description of the asset. The weakest is a description of the bonus.

If the desk needs both

Some desks genuinely need trading and optimisation in one seat, usually small desks where headcount is the binding constraint. That person exists, the trader-optimiser hybrid, and commands a premium over either single profile, because both sides of the market bid for them and neither can grow the supply. The census will say honestly whether your market holds any, and in most markets the pool is thin enough to plan around rather than depend on. The realistic choices are two hires in sequence, or one hybrid found through a longer and dearer search, or a structure where a strong optimiser works alongside the existing traders with the seam managed deliberately.

What the market will not supply, at any salary, is a trader who stops being a trader because the job advert asked nicely. The occasional trader who converts well was already the exception that proves the scoping point: they wanted the other job, and preference did the converting, not price. The desks that have learned this scoped the role once, correctly, and kept the person. The desks that have not are on their second search with the first brief, wondering why the pool looks empty. The pool is not empty. It is standing outside the definition.