Senior Data Scientist Data and Insights · London · Hybrid Remote

loveholidays
London
2 weeks ago
Create job alert

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 seven members, including two Senior Data Scientists, four Data Scientists, 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 Senior Data Scientist will play a pivotal role in propelling loveholidays forward. Positioned within a team of passionate data enthusiasts, you'll be instrumental in shaping our data-driven strategies and outcomes.

Your day-to-day:

  • Researching and developing new models and techniques to tackle key business challenges
  • Overseeing the production and maintenance of systems
  • Conducting code reviews and collaborating on various projects across teams
  • Providing mentorship and coaching, facilitating career growth within the team
  • Engaging in project rotation for a fresh perspective and sustained engagement
  • Proposing new initiatives and collaborating in team OKR crafting
  • Participating in morning stand-ups and weekly prioritisation meetings

Your skillset:

We're on the hunt for a driven individual who employs a scientific approach to data, where the following qualities are paramount:

  • Excellent problem-solving skills:Tackle a wide array of challenges through independent work and collaboration
  • Innovation and curiosity:Work across the business to understand challenges and develop practical solutions
  • Self-starter:Identify issues and opportunities independently, constantly seeking to learn and innovate
  • Team player:Collaborate effectively, accept feedback, and provide mentorship
  • Communication skills:Influence stakeholders and articulate data science concepts to non-technical audiences

Required Experience

  • Leading E2E projects, from inception, planning/prioritisation to delivery including monitoring and alerting
  • Designing experiments and modelling to generate actionable insights and enhance business performance
  • Proficient in machine learning and statistical methods for predictive modelling and forecasting
  • Experience deploying ML models to production at scale
  • Solid understanding of SQL
  • Proficiency in unit testing, CI/CD, model management and experiment tracking

Desirable

  • Experience with Deep Learning, Generative AI and Reinforcement Learning
  • Experience with Time Series Forecasting and Recommender Systems
  • Previous experience working in e-commerce, retail, or the travel industry.
  • Conducted and analysed large scale A/B experiments
  • Experience mentoring team members
  • Experience with workflow orchestration technologies such as Airflow, Dagster or Prefect
  • Experience with technologies such as:
    • Google Cloud Platform, particularly Vertex AI
    • Docker and Kubernetes

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 - 30 mins
  • 1st stage with Hiring Manager - 45 mins
  • Take-home exercise presentation - 1 hour
  • Final stage with key stakeholder/s including a task to present, in office - 1 hour

#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Scientist Engineering & Tech · Mumbai · Hybrid Remote

Lead Data Scientist

Senior Machine Learning Scientist

Senior Analyst - Fraud Models Management

Chief Technology Officer (CTO)

Data Science and Analytics Senior Business Analyst

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Careers

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.

Careers

Data Science Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Data science has become a linchpin in modern business, transforming oceans of raw data into actionable insights that guide strategy, product development, and personalised customer experiences. With this surge in data-centric operations, the need for effective data science leadership has never been more critical. Guiding a team of data scientists, analysts, and machine learning engineers requires not only technical acumen but also the ability to foster collaboration, champion ethical practices, and align complex modelling efforts with overarching business goals. This article provides practical guidance for managers and aspiring leaders aiming to excel in data-driven environments. By exploring strategies to motivate data science professionals, develop mentoring frameworks, and set achievable milestones, you will be better prepared to steer your team towards meaningful, evidence-based outcomes.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.