Offices:
United Kingdom
81 Judes Road
Egham TW20 ODF
Latvia:
Teamence Ltd.
no. 40203237813,
Zalites Str. 50, LV-2111
Two fintech companies. Both needed a Data Scientist. Both made a great hire. But one search took 4 months and 226 candidates approached, and the other took 1 month and 95. Same market, same kind of profile, same recruitment team. So what made the difference? Dana Kocane, Founder of Teamence, looked back at both searches with her team to find out.
Kocane has more than 16 years of experience in HR and recruitment across IT and fintech. Her team at Teamence runs searches for tech and fintech companies in Europe, the Nordics and the Baltics.
On paper, both searches ended the same way: one strong hire. The path there looked very different.
Company A - 226 candidates approached, 20 first interviews with Teamence, 12 candidates sent to the client, 1 hire, 4 months.
Company B - 95 candidates approached, 6 first interviews with Teamence, 3 candidates sent to the client, 1 hire, 1 month.
"Both companies hired a strong Data Scientist. But one search was very successful, and the other was too complicated. When we looked back, it came down to five things."
Company A has a very progressive data team and ambitious goals. But the profile they wanted hardly exists in the market, and the few people who have it get offers every week.
Company B also looked for strong people, but with good potential. A slightly different profile, not a unicorn.
"When you look for a unicorn, either open the profile to people who can grow into it, or make sure you can pay what the rare ones cost."
A hire starts at the top. In Company A, the leaders didn't fully agree on what this person should do. As a result, the brief moved, feedback waited and decisions took longer.
In Company B, leadership agreed on the hire before the search started. The team knew what they needed, and every candidate was measured against the same picture.
Rare people have options, and they choose the place that fits their life. Strict work conditions narrow an already small market even further.
"Strict work conditions don't work for unicorns. In Company B, the conditions were flexible enough for the right person to say yes."
Good Data Scientists don't wait. While one company takes a week to reply, another one sends an offer.
In Company B, quick answers after each interview kept candidates interested and moving. In Company A, some strong people went cold while they waited for the next step. Each lost candidate meant going back to the market and starting again.
Company A needed 12 candidates sent to get one yes. Company B needed 3.
"A salary range agreed with the market at the start saves months. It's much easier to adjust the offer before the search than after the third candidate says no."
A realistic offer doesn't always mean a higher one. It means one that matches the profile you're asking for.
It would be easy to read this as a story about a good company and a bad one. It isn't. Both are great places to work.
"It's about the process around the hire. And HR, hiring managers and recruiters build that process together."
HR knows the company and its culture. The hiring manager knows the team and the work. The recruiter knows the market. When all three agree early, the search moves faster.
Progressive companies that want progressive talent often need more time and more resources to find that person. That's normal. If you want to hire a Data Scientist faster, the setup makes the difference: a profile the market can deliver, leaders who agree on the hire, conditions that attract rare people, quick feedback and an offer that fits the profile. Get these five right before the search starts, and a four-month search can become a one-month one.
At Teamence, we help tech and fintech companies with Data Scientist recruitment and build a hiring process that works for both sides. If you're planning a data hire, we'd be happy to start with the brief.