We casted our net at scale: using 533 keywords to map 1778 companies. This returned almost 50k profiles, out of which our software scanned 38k to distil only the top 5% matches. With a 77% accuracy rate, it didn't take us long before we could finalise a Long List!

Within the constraints of time allocated to this hire, we had to make a trade-off between:

• Mapping the local Talent market, as the preference was to have the role located in the R&D Lab in Sydney. However, there was a high risk that the high calibre Talent we were after would not exist in Australia

• Exploring the US Talent market, even though we didn't know what to expect and where to even start!

Our data insights informed the rationales to make a data-driven decision, in consultation with our client.

We submitted to the business a sample of the Top profiles we had identified in each location, for review. With their feedback we established a rating, from 0 (low interest) to 4 (perfect match).

Leveraging our curated search results (~1700 profiles in California), we looked at the type of companies which employ our target profiles. The above reveals that the vast majority (80%) was part of organisations comprising of +500 employees.

Knowing what competition we'd be facing, we realised that we had to adapt our budget strategy. In complement to our salary benchmarking, we conducted a salary survey of the below companies:

Through sampling profiles for each of these Top companies, we formed market intel' by learning from the technologies in use, level of advancement / maturity and further our knowledge of renown programs & projects happening in the market.

We then provided the business with a Competitor Analysis.

This allowed us to, both:

• Identify companies onto which focus our headhunting efforts

• Encover alternative Talent markets by looking at more accessible industries where Talents had transferable skills.

We took a closer look at the demographics of our target Talent market:

Being an engineering startup, our IP is a highly valuable asset protected by patents. A considerable proportion (more than a quarter) were PhD holders. One could presume that they'd be familiar with publishing scientific papers and filling patents.

This also informed our search strategy: we included Google Scholar, IEEE and ResearchGate to our search tactics

By profiling our target audience, we were able to:

• Feedback to our client what they could expect (e.g. skillset, demographics, level of proficiency, etc). This subsequently allowed the hiring Manager to revisit the Profile Description and, Executives to review the scope of the project

• Attune our communication & reach outs: 1 in 4 persons contacted replied to us (cf. Search Funnel)! Given the relatively low brand awareness our client had in the US market, this was very exciting!

Looking the academic background, informed of the following:

• Prospective candidates graduated from the Ivy league, which conforted our assumptions around salary

• We realised that a fair proportion was coming from Texas; which led us to steer our search in this direction

This unhearted the following four clusters:

• Texas (Houston, Dallas, Austin)

• East Coast of the US (Washington, NYC)

• Europe (from London to Switzerland (Paris, Germany, the Netherlands) and around in South Scandinavia (Denmark, Warsaw, Prague)

• South of India

Finally, had our client wished to hire in volume, this could have served as the basis of setting up a Talent Pool!

You want to know more?