• Own the connected-growth product strategy for US Valve’s data center business • Identify opportunities where broader IDEX products, technologies, or capabilities can support data center cooling applications • Build strong working relationships with other IDEX business units to understand their products, capabilities, limitations, and commercial fit • Partner with Sales and Business Development to understand customer needs, application gaps, and market opportunities • Translate customer and market needs into clear product, portfolio, and commercialization opportunities • Build business cases for connected-growth opportunities, including market need, customer value, revenue potential, margin expectations, investment needs, risks, and execution requirements • Partner with Finance to validate assumptions around revenue, margin, cost, pricing, investment, and payback • Work with Engineering and Operations to understand whether connected-growth opportunities are technically and operationally realistic • Support commercialization planning for connected-growth products, including positioning, customer messaging, sales tools, launch plans, and trade show support • Help determine which opportunities should be built by US Valve, sourced through another IDEX business, partnered externally, or considered as a future M&A capability gap • Support M&A strategy by helping identify product gaps, technology adjacencies, market needs, and potential capability areas that could strengthen US Valve’s position in data center cooling • Maintain a clear pipeline of connected-growth opportunities, including status, next steps, owners, risks, and expected business impact • Help prioritize connected-growth opportunities using market size, customer pull, margin potential, strategic fit, speed to market, and execution complexity • Partner with the current Product Manager to ensure connected-growth opportunities fit with the broader US Valve product roadmap and do not create confusion with US Valve-made products • Support customer meetings, trade shows, and IDEX cross-business discussions where connected-growth opportunities are being developed • Bring structure, clarity, and follow-up to ideas that might otherwise stay informal or get lost between business units

• Serve as the DM study lead and the primary point of contact for clinical study teams and external partners • Oversee all DM activities across all stages of the trial from study start-up through archiving • Provide a high level of expertise in data management to support clinical studies • Provide clear verbal or written information and hands-on support to project team members and to CROs related to eCRF and database design, data quality, and reporting of database / data quality status • Oversee the implementation and execution of procedures for data quality review and data acceptance prior to data analyses and/or database lock • Manage data transfers with CROs and third-party data sources, SAE/AE reconciliation and MedDRA/WHO-DD coding • Support the transfer, locking, and archiving of study databases • Manage scheduling and time constrains across multiple projects • Prepare recommendations for new or improved processes for data management and data flow • Document DM sponsor oversight activities from protocol review through study close-out

• Design, build, and scale advanced detection and diagnostic models for solar and storage assets. • Enable faster detection, fewer truck rolls, and better customer experience. • Report to the Director of Data Science and partner closely across product management, engineering, and operations to take models from idea to production in Omnidian’s Resolv platform.

• Conduct data discovery and exploratory data analysis across structured and unstructured data • Perform data cleansing, normalization, aggregation, and modeling • Design and build analytic applications in Palantir Foundry, including dashboards and interactive workflows • Apply advanced analytics and statistical methods such as regression, clustering, hypothesis testing, and A/B testing • Develop and embed AI/ML capabilities (LLMs, NLP, RAG/GraphRAG) into analytic workflows • Create clear visualizations and metrics to support executive and operational decision‑making • Collaborate in an Agile/Scrum environment to rapidly iterate on solutions • Communicate insights effectively to both technical and non‑technical stakeholders