Senior Data Scientist

Our Ways of Working Principles:

We believe that most of us do our best work when we work together, but we know that everyone works in different ways, and quite frankly, has other commitments and responsibilities outside of work.

As we further adjust to hybrid working, we want to take what we've learnt from working remotely and keep the flexibility that's enabled us to thrive and keep driving our business forward.

We have some core principles which support us in this:

Do what’s right

Trust & give permission

Delivery matters

We understand ways of working can look different based on your role, team and you as an individual so we are here to support and discuss this with you during the interview process.

Work with us

At Moonpig Group our mission is to help people connect and create moments that matter. We’re an international group made up of three brilliant brands – Moonpig in the UK, Ireland, US and Australia, and Greetz in the Netherlands – with our newest addition Buyagift joining us in 2022.

We were founded with a goal to disrupt the traditional greetings industry. Two decades on, we’re an established leader within the online gifting market, offering a wide range of products to customers across the world.

Moonpig is an iconic brand and innovator, with clear values (read more about our values here!). These values set our teams and our business up for success in an environment that’s fun, supportive and challenging. They’re the glue that binds us together and we think of them as a platform to help us deliver our best work. You have every chance to drive impact here at Moonpig, and most importantly, we genuinely want you!

Our architecture is built for scale and flexibility which will allow us to quickly innovate and launch new propositions - coupling that with the wealth of data we have on our customers, the sky's the limit in the world of experimenting with cutting edge ideas

What You’ll Be Doing

We’re looking for an experienced Data Scientist to work with our innovative Data Science, Product and Engineering Teams, to drive the evolution of our on-site search capabilities. Building on top of our existing Vector Search capabilities, you’ll use Natural Language Processing (NLP) techniques to enhance our understanding of customer queries to deliver highly relevant and personalised search results. You'll continually validate your hypotheses through A/B testing, ensuring we provide an intuitive and satisfying search experience that helps our customers make moments that matter. You will also have the opportunity to bring your expertise to our rich text-based dataset across a variety of projects outside of Search, as part of the wider data science team.

Key Responsibilities:

• Design, implement, and fine-tune innovative search algorithms to improve search relevance, accuracy, and performance.
• Develop and optimise NER models to better understand and classify entities within user queries, enhancing semantic search capabilities.
• Design and implement models and algorithms to handle user typos and misspellings, ensuring robust and user-friendly search experiences.
• Build and refine models that suggest relevant search queries based on user inputs and context to improve user search experience.
• Develop algorithms to identify and surface trending searches based on user behaviour and historical data.
• Leverage vector search techniques to enhance semantic understanding and retrieval performance of user queries.
• Conduct detailed data analysis to identify search performance issues, and design A/B tests to validate improvements and new features.
• Work closely with our Search product management, engineering, and UX teams to define search-related requirements, priorities, and implementation strategies.
• Contribute to the wider Data Science team through knowledge sharing and peer review, and, where appropriate, working on projects that require your expertise outside of the Search team
• Keep abreast of the latest advancements in machine learning, NLP, and search technologies to continuously evolve and improve the search platform.

You'll be a great addition to the team if you:

• Have 3+ years of experience as a Data Scientist using Natural Language Processing (NLP) techniques. Including: You have used Named Entity Recognition (including tokenization, Part-of-Speech tagging, feature extraction and modelling) to detect and classify entities within a text. Additionally, you have experience with fuzzy matching algorithms like Levenstein distance and n-grams for handling spelling errors and typos.
• You have a range of general machine learning experience, and are proficient in building and fine-tuning complex models, including feature engineering, and hyperparameter tuning. You have a deep understanding of model evaluation and validation techniques, ensuring robustness and generalizability of models.
• Python expert and excel at writing highly efficient, production-ready code. You use your knowledge of software engineering best practices such as testing, continuous integration (CI), and version control to build end-to-end machine learning systems that are both scalable and maintainable.
• Are a great communicator, able to summarise your findings to non-technical stakeholders effectively.

More about you:

• Previously used Vector Embedding Models like Word2Vec, GloVe, FastText, BERT, GPT, or transformer-based sentence embeddings to represent text in vector space.
• Previous experience with Search in an ecommerce environment, including traditional keyword search (like Elastic Search) and Vector Search.
• Previous experience with implementing Learning-to-Rank algorithms in an ecommerce context.
• Always curious and looking for ways to learn new things. When we want to develop a novel solution for handling typos, you dive into the published research and figure out how we could translate cutting edge methodologies to our own systems.
• Able to explain complex data science concepts in a clear and persuasive way. Imagine you're advocating making significant changes to our approach to Named Entity Recognition, and a non-technical stakeholder challenges your recommendation. You can clearly articulate the benefits, risks and tradeoffs of your solution, turning this stakeholder into a trusted champion for your work.
• Great team player with impeccable collaboration skills. When you're investigating how we might improve our contextual search suggestions, you share your ideas with the team and seek feedback early and often, bringing others on the journey with you.
• Have a commercial mindset. If you need to decide between building a large, game-changing solution, or a small iterative change, you know how to balance achieving the best possible model performance against pragmatic business needs.
• Comfortable working in a fast-paced environment. If you're working on a big project, and external circumstances change, you can quickly pivot to take advantage of the new opportunity.
• Embrace a test-and-learn approach. When you've got a new idea for how our spellchecker can be improved, you find a way to quickly validate your hypothesis. If your idea doesn't work, that's fine - it's a learning opportunity and you'd rather learn quickly than worry about creating the perfect solution.

Want to hear more?

Find out more about Moonpig Group and what it has to offer here!

Moonpig’s Commitment to Equality, Diversity and Inclusivity

At Moonpig Group, we’re committed to creating an inclusive and caring culture with brilliant people who feel a real sense of belonging. We welcome and celebrate all diverse backgrounds to Moonpig Group, from working parents who need flexibility with their hours to individuals who are neurodiverse and prefer to work a certain way.

We’re proud to have several employee-led committees within our organisation, including the LGBTQ+, Gender Balance, Neurodiversity and our EMBRACE (Educating Myself for Better Racial Awareness and Cultural Enrichment) Committees.

We’ll continue to push for diversity and that sense of belonging so that all Moonpig Group employees feel safe and comfortable to be their true authentic self at work.