
Talent Scientist
3 weeks ago
As a pioneer remote-first tech company with a product that inspires people globally, we attract a huge number of applicants to our organisation. We have created a hiring process that is totally unique empowering our business based Hiring Leadership team to lead talent selection. Our Talent Science team ensures that our processes are effective and that the business is able to make the best decisions to select exceptional talent. This is an exceptional opportunity to join a team that is changing the way an organisation hires.
Our Talent Science team has a mission to ensure that we follow objective, scientifically rigorous and efficient processes to select the very best new colleagues regardless of location, culture or background. We work closely with our key stakeholders to ensure that decisions are being made in the right way and that our hiring model supports the selection of world class talent, regardless of location, culture or background.
As a Talent Scientist, you will work closely with these Hiring Leads to drive initiatives, automation and best practice whilst offering an expert viewpoint on talent assessments. This is not a recruiter position; it's about the science of talent and performance, raising awareness and insights across the business so that they are able to select the best talent available from our global talent pool.
We have a number of mid level openings in our team seeking the following:- Passionate about how an organisation selects talent using scientific approaches
- Ability to interview candidates using behavioural interviewing techniques (competency based and psychometric assessments)
- Strong analytical problem solving ability to identify trends and patterns using R or Python, SQL, statistical analysis, BI tooling etc.
- An exceptional academic background including a Bachelors or Masters degree in a Psychology based subject
- A high level of personal organisation to work remotely and be effective
Location: EMEA - Home based
What your day will look likeAs a Talent Scientist you will:
- Drive talent analytics to provide our business with real-time insight, partnering with the business to help them move through their hiring processes efficiently.
- Conduct in-depth behavioural talent interviews providing considerable insights into motivations and behaviours.
- Build key relationships with global stakeholders to ensure we deliver against our hiring agenda, closely monitoring hiring activities, driving results and ensuring that there is consistency in our operational processes.
- Drive data driven insights, making sure our decision making process is robust and supportive to inform our decisions.
- Consider our employer brand and how our interactions with a candidate impacts their experience.
- Review and streamline hiring processes and tools to drive continuous improvement.
- Work with external third parties and platforms to ensure we maximise our return on investment.
- Bring a passion for diversity and inclusion, ensuring we remove unconscious bias from our hiring process and ensuring our sourcing strategy underpins this.
- An exceptional academic background including a Bachelors or Masters degree in a Psychology based subject.
- Strong analytical problem solving ability to identify trends and patterns using R or Python, SQL, statistical analysis, BI tooling etc.
- Exposure/appreciation of psychometric assessments, including interpretation.
- Experience of conducting behavioural, competency based interviews with the ability to train stakeholders and advise on how to get the best out of an interview.
- An demonstrative viewpoint on talent, with a deep appreciation of how to predict and measure success of people.
- Passionate about how an organisation selects talent using scientific approaches.
- A high level of personal organisation to work remotely and be effective.
- Willingness to travel to company events 2-4 times a year, for up to two weeks each.
- Experience in sourcing and headhunting with the ability to teach our senior leadership team how to hunt for industry leaders.
- Experience in statistical significance testing and experience in Bayesian inference and/or predictive analytics and ML.
- Exposure to the following tools: LinkedIn Talent Insights, Greenhouse, DISC profiling.
- Psychometric validity and reliability metrics.
We consider geographical location, experience, and performance in shaping compensation worldwide. We revisit compensation annually (and more often for graduates and associates) to ensure we recognise outstanding performance. In addition to base pay, we offer a performance-driven annual bonus. We provide all team members with additional benefits, which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally.
- Distributed work environment with twice-yearly team sprints in person.
- Personal learning and development budget of USD 2,000 per year.
- Annual compensation review.
- Recognition rewards.
- Annual holiday leave.
- Maternity and paternity leave.
- Employee Assistance Programme.
- Opportunity to travel to new locations to meet colleagues.
- Priority Pass, and travel upgrades for long haul company events.
Canonical is a pioneering tech firm at the forefront of the global move to open source. As the company that publishes Ubuntu, one of the most important open source projects and the platform for AI, IoT and the cloud, we are changing the world on a daily basis. We recruit on a global basis and set a very high standard for people joining the company. We expect excellence - in order to succeed, we need to be the best at what we do. Canonical has been a remote-first company since its inception in 2004. Working here is a step into the future, and will challenge you to think differently, work smarter, learn new skills, and raise your game.
Canonical is an equal opportunity employer. We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration.
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