Following the design of more efficient blockchain consensus algorithms, the execution layer has emerged as the new performance bottleneck of blockchains, especially under high contention. Current parallel execution frameworks either rely on optimistic concurrency control (OCC) or on pessimistic concurrency control (PCC), both of which see their performance decrease when workloads are highly contended, albeit for different reasons. In this work, we present NEMO, a new blockchain execution engine that combines OCC with the object data model to address this challenge. NEMO introduces three core innovations: (i) a greedy commit rule for transactions that do not use shared objects; (ii) refined handling of dependencies to reduce re-executions; and (iii) the use of incomplete but statically derivable read/write hints to guide execution. Through simulated execution experiments, we demonstrate that NEMO significantly reduces redundant computation and achieves higher throughput than representative approaches. For example, with $\mathbf{1 6}$ workers nemo’s throughput is up to $42 \%$ higher than the one of BlockSTM, the state-of-the-art OCC approach, and 61% higher than the pessimistic concurrency control baseline used.