Manager, Talent Science at Canonical

Responsibilities

• Lead a team of data driven behavioural experts, responsible for ensuring that our leadership teams are selecting  game changing talent for our organisation.
• Drive analytics projects that bring deep insight and understanding to how we select talent, based on examining performance indicators and outcomes.
• Build key relationships with global Hiring Leadership stakeholders to drive our hiring agenda.
• Be seen as a thought leader on talent initiatives with an inherent belief that past performance predicts future success.
• Conduct in-depth behavioral talent interviews providing considerable insights into motivations and behaviours of talent.
• Review our assessment effectiveness to drive continuous improvement.
• Ensure our Employer branding and DEI initiatives support and drive an inclusive environment for our people.

Requirements

• An undergraduate or postgraduate degree in psychology/industrial psychology, or a compelling narrative about your alternative chosen path, together with an exceptional academic track record throughout your education years.
• Strong analytical mindset with solid evidence of driving analytical projects and storytelling through data to drive change ideally from in the Technology space.
• Skilled in R or Python, SQL and building BI dashboards.
• Exceptional management experience, leading analytical mindsets and projects that drive efficiency and deliver results. 
• A thought leader in the talent space with the ability to influence best practice, bringing a solid point of how to build a high performance organisation.
• Good exposure to key talent topics: competency based interviews, psychometric assessments, employer branding, candidate experience, DEI.
• Proven ability of working with senior stakeholders to drive a professional outlook on hiring talent  as well as challenge the status quo.
• Experience of successful configuration of hiring tools that enable the selection process.
• Willingness to travel up to 2-4 times a year for internal events.

Skills

• Experience in statistical significance testing and experience in Bayesian inference and/or predictive analytics and ML.
• Experience on building data dashboards.
• Exposure to the following tools: Jira, LinkedIn Talent Insights, Greenhouse, DISC profiling

Benefits

• 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