\textit{Interactive theorem provers} (ITP) enable programmers to formally verify properties of their software systems. One burden for users of ITPs is identifying the necessary \emph{helper lemmas} to complete a proof, for example those that define key inductive invariants. Existing approaches to \emph{lemma synthesis} for ITPs have limited, if any, support for synthesizing \emph{implications}: lemmas of the form $P_1 \land \cdots \land P_n \implies Q$. In this paper, we propose a technique and associated tool for synthesizing useful implication lemmas. Our approach employs a form of data-driven invariant inference to explore strengthenings of the current proof state, based on sample valuations of the current goal and assumptions. We have implemented our approach in a Rocq tactic called dilemma. We demonstrate its effectiveness in synthesizing necessary helper lemmas for proofs from the Verified Functional Algorithms textbook as well as from prior benchmark suites for lemma synthesis.