Staff Data Scientist Data and Insights · London

Why loveholidays?
At loveholidays, we’re on a mission to open the world to everyone, giving our customers’ unlimited choice, unmatched ease and unmissable value for their next getaway. Our team is the driving force behind our role as our customers’ personal holiday expert - the smart way to get away.
About the team
Our Data Science team comprises eight members, including four Senior Data Scientists, two Data Scientists, a Machine Learning Engineer and the Head of Data Science. We specialise in various areas such as Recommender Systems, Time Series Forecasting, Deep Learning, and Reinforcement Learning, fostering a collaborative learning environment.
Our focus is on modelling and problem-solving, leveraging advanced machine learning techniques to create solutions to challenging business problems. We prioritise clean, well-tested code with a culture of documentation and knowledge sharing. Our tech stack includes GCP, Python, GitHub, PyTorch, TensorFlow, Scikit-learn, and XGBoost.
With mature infrastructure and dedicated teams for Data Engineering, Analytics, and Platform Engineering, our Data Scientists enjoy high autonomy. We tackle interesting datasets, set up large-scale experiments, and implement growth strategies with NO red tape. Quarterly OKR planning ensures that priorities are clearly defined and teams are aligned on objectives.

The impact you’ll have:
Reporting to the Head of Data Science, the Staff Data Scientist will be a technical leader who drives strategic initiatives and shapes the technical direction of the Data Science function at loveholidays. You'll be a catalyst for innovation, a mentor to junior team members, and a trusted advisor to stakeholders across the business, helping to implement our AI strategy and align data science capabilities with business objectives.
Your day-to-day:
Leading strategic initiatives from conception to delivery, including stakeholder management and business value articulation

Researching and developing cutting-edge models and techniques to tackle complex business challenges

Establishing and implementing best practices across data science systems and services

Providing technical leadership and mentorship to junior team members, facilitating their growth and development

Proactively identifying and implementing improvements to team processes or workflows

Contributing to architectural decisions for data science infrastructure

Leading knowledge sharing sessions through technical presentations of projects

Representing data science in cross-functional initiatives and being a trusted advisor beyond your immediate team

Participating in project prioritisation and strategic planning for the data science function

Implementing comprehensive monitoring solutions and designing fault-tolerant systems

Your skillset:
We're seeking an exceptional technical leader who can drive innovation while maintaining production excellence. The following qualities are essential:
Technical Excellence:

Deep expertise in machine learning approaches with the ability to assess and implement cutting-edge algorithms

Strategic Thinking:

Ability to break down high-level optimisation goals into lower-level components whilst understanding complex/second-order consequences

Leadership:

Proven ability to mentor others, resolve conflicts, and be a key motivator for team members

Business Acumen:

Strong ability to link technical solutions to business outcomes and prioritise work based on impact

Communication:

Exceptional ability to translate complex technical concepts to non-technical stakeholders and influence decision-making

Problem-Solving:

Track record of resolving complex technical challenges that impact multiple teams

Collaboration:

Demonstrated success working across functions and teams to deliver high-impact projects

Required Experience
Leading multiple end-to-end projects simultaneously, from inception through to production monitoring and optimisation

Designing and implementing sophisticated experiments and models that significantly enhance business performance

Expert-level knowledge of machine learning and statistical methods for predictive modelling and forecasting

Extensive experience deploying ML models to production at scale with robust monitoring systems

Advanced knowledge of SQL and data manipulation techniques

Mastery of software engineering best practices including unit testing, CI/CD, model management and experiment tracking

Track record of successful technical mentorship and team development

Demonstrated cross-functional collaboration skills across engineering, product, and business teams

Desirable
Expertise in Deep Learning, Generative AI and Reinforcement Learning

Advanced knowledge of Time Series Forecasting and Recommender Systems

Previous experience working in e-commerce, retail, or the travel industry

Experience designing and analysing large-scale A/B test experiments

Mastery of workflow orchestration technologies such as Airflow, Dagster or Prefect

Expert knowledge of technologies such as:
Google Cloud Platform, particularly Vertex AI

Docker and Kubernetes

Infrastructure as Code

Experience establishing data science best practices across an organisation

Perks of joining us:

Company pension contributions at 5%.

Individualised training budget for you to learn on the job and level yourself up.

Discounted holidays for you, your family and friends.

25 days of holidays per annum (plus 8 public holidays) increases by 1 day for every second year of service, up to a maximum 30 days per annum.

Ability to buy and sell annual leave.

Cycle to work scheme, season ticket loan and eye care vouchers.

At loveholidays, we focus on developing an inclusive culture and environment that encourages personal growth and collective success. Each individual offers unique perspectives and ideas that increase the diversity and effectiveness of our teams. And we value the insight and potential you could bring on our continued journey.
The interview journey:

TA screening with someone from our Talent team - 30 minutes

1st stage interview with the Head of Data Science - 45 minutes

Panel interview with key stakeholders, including a task to present in office - 1.5 hours

Final stage with Chief Data Officer - 45 minutes

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