Data Science Manager, tem

• Proven experience managing ML engineers or scientists (not just software engineers) at varying ranges of experience (Junior to Staff), with enough understanding of the ML lifecycle and core disciplines including forecasting, optimisation, pricing, and classical ML to manage credibly
• A strong people development track record: 1:1s and performance conversations that actually move people forward, action underperformance, clear progression frameworks, and coaching that builds capability across engineers at different career stages
• Experience building and owning team operating systems: the prioritisation frameworks, sprint cadences, incident review processes, and feedback loops that make a technically complex team perform consistently
• A strong hiring instinct for ML roles: you have defined the bar, built pipelines in a competitive market, and brought in strong people who had other options
• Experience managing a technically diverse team: comfortable holding substantive conversations across different ML problem types and helping a multi-disciplinary team prioritise and operate without being the expert in any single domain
• Experience in a startup or high-growth environment: comfortable with ambiguity, able to operate effectively when not everything is figured out, and ready to do more than a textbook people-manager role at a larger organisation would require

Desirable

• We're looking for a Machine Learning Manager to lead the people side of tem's most technically complex team
• Rosso is tem's core IP: the AI-powered engine at the heart of how we price, forecast, and optimise energy transactions. The ML engineers who build it work across multiple distinct specialisations simultaneously: time-series forecasting, pricing, optimisation, and classical ML. The work is technically complex and commercially critical
• This role exists because the ML engineers need a dedicated, full-time leader focused entirely on their growth and performance. This is a people leadership role, not a technical authority role. The ML engineers are the experts. Your job is to create the conditions where they can do their best work: clarity, coaching, the right operating systems, and a strong hiring bar as the team grows. You will act as a sounding board, not a reviewer. You will work closely with the Rosso Engineering Manager to ensure the ML and software engineering sides of the service collaborate well
• Tem is a Series B company and this is a startup environment. The lines are less rigid than they would be at a larger organisation, and the person who thrives here will be comfortable with that
• In your first 12 months, success looks like this: you have built trust with the ML engineers and established yourself as their go-to leader; the team has clear operating rhythms, a strong feedback loop between production monitoring and development priorities, and a predictable hiring pipeline; each engineer has a clear development path; and the collaboration between ML and software engineering within Rosso is noticeably stronger
• Build a high-performing ML team: Lead hiring, onboarding, performance management, and career development. Set the frameworks, operating rhythms, and succession plans that give ML engineers clarity, support, and room to grow. You are the person who makes sure the team is getting the leadership attention it needs
• Own the team's operating systems: Build and maintain the rituals and structures that keep the team effective: sprint cadences, incident review, model monitoring feedback loops, cross-team reporting, and the prioritisation processes that keep the team focused on what matters
• Enable technical excellence without owning it: Act as a sounding board for ML engineers on questions and blockers. Ask the right questions, help surface risks, and create space for the experts to make good decisions, without adding another review layer or positioning yourself as a technical authority
• Drive collaboration with the Rosso Engineering Manager: Partner closely to align priorities between the ML and software engineering teams within the service. The two teams need to work together effectively, and you are a key part of making that happen
• Represent the team and champion tem's culture: Communicate progress, risks, and priorities clearly to the broader organisation. Lead with intention in a fully remote environment, champion what excellent remote work looks like, and represent tem in the ML community when recruiting and engaging externally

• Our processes normally take around 2-3 weeks from first call to offer - please let us know about any adjustments to timelines that may be required
• First call with our Talent Team (30 mins). This is to understand your experience, motivations, and discuss the role in more detail
• Behaviour Interview with our Head of Data (45 mins). This is your chance to really understand the role, the expectations, and ensure alignment on ways of working
• Skills Interview with the Team (75 mins). You'll meet with potential peers in this session and will discuss how you lead and manage high performing teams, and discuss a range of scenarios
• Culture-Add Interview with Stakeholders (45 mins). The final session will be with two cross-functional stakeholders, and will explore how your values align with ours, and is designed to be a genuine two-way conversation, your chance to understand what it's really like to work at tem