Loveholidays is on a mission to build the next generation of online travel agents. We let millions of customers search through over 36 billion offers that we curate and are constantly exploring new and innovative ways to create that perfect holiday-finding experience.
In 2019 we were the fastest growing company in the UK, and since the beginning of 2022 we have been processing a booking every ~30 seconds.
About the role
🌱 Our Data Scientists use data to help boost an already rapid business growth trajectory, to make better decisions, faster by using machine learning and data science techniques. This encompasses data cleaning/joining, feature engineering, model training, data pipelines/scheduling, and communicating results to the business.
📈 We need you to set up, monitor and track large scale experiments and come up with machine learning techniques to drive business outcomes. Our Data Scientists work closely with other business units to deliver day to day trading results and engage with stakeholders and the team to plan meaningful steps to increase conversions, traffic and margins.
✅ With the high maturity of our infrastructure you will have a high level autonomy, working with interesting and challenging data sets, thinking about what can be implemented for growth and do it with NO red tape.
We are looking for an ambitious individual with a passion for leveraging a scientific approach to data to drive business transformation. Domain knowledge and expertise are important, but the following core attributes are essential:
- Excellent problem-solving: apply their mind to many and varied problems and looks for the impactful solving of them through a combination of individual contribution and working with a range of parties
- Innovative and curious: engage with colleagues from across the business, to understand their business issues, and facilitate practicable solutions
- Self-starter: proactively seek out issues and opportunities and tackle them to learn and find new and better ways of doing things
- Team player: work with other people in the team, take in feedback and mentor other people
- Communication skills: able to influence and coordinate well with business stakeholders and present data science work to non-technical audiences
Required experience for this role:
- Design experiments and implement models to produce practical insights and improve business performance
- A deep understanding of Machine Learning and statistical techniques for predictive modelling and forecasting - we apply machine learning and statistics to achieve business outcomes
- Write high-quality Python for feature engineering and model training.
- Solid grounding in SQL
You’d get bonus points if you have:
- Previous experience working in e-commerce, retail, or the travel industry.
- Experience with time-series forecasting
- Worked with Airflow
- Conducted and analysed large scale A/B experiments
- Experience with technologies such as:
- Google Cloud Platform, particularly Vertex, Looker, and Datastudio
- Docker and Kubernetes
- Understanding of causal inference and/or reinforcement learning
Other than an amazing environment for you to grow, have impact and show the world your incredible skills, we offer the following benefits:
- Company pension contributions at 5%
- 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 of 30 days per annum
- Ability to buy and sell annual leave
- Subsidised gym memberships
- Cycle to work scheme, season ticket loan and eye care vouchers
- Hybrid working - we work 2 days per week from our office in Hammersmith
- Monthly office based social events
- Weekly Wednesday drinks in the office kitchen
- Sustainably sourced fruit baskets in the office kitchen
- Data & Insights
- Data Scientist
- Remote status
- Hybrid Remote
Our London HQ is an open-plan office in Hammersmith. We are just 5 minutes walk from the river and have great meeting spaces and plenty of break-out areas.
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