Job Description
Senior Data Scientist - Hybrid Working - London/Home
Why join us
In Customer Data Science (part of the Data Science Hub), we build the systems behind personalised customer decisioning – from customer segmentations to offer optimisation. We impact millions of customers, bringing them value and earning their loyalty.
This team already personalises all of the offers you see in the Nectar app, but now we’re growing in ambition and scale. We aim to personalise everything that matters – offers, online recommendations, digital experiences, communications. And we aim to achieve this using our incredible data asset, our rich customer understanding, and state of the art machine learning and AI.
This role will work in a team dedicated to personalising customer experiences within the Nectar loyalty programme and optimising large-scale offer decisioning systems across a range of touchpoints. As one of the senior individual contributors in the team, you’ll apply your wealth of experience and ideas to design, build, and improve our capabilities – driving value for the customer and the business.
What you’ll do
Solve the hard problems
Lead on the technical development of algorithms and pipelines that will deliver against our strategic objectives.
Iterate our modelling and optimisation capabilities, identifying the most appropriate techniques to enable continuous learning, expansion to novel mechanics, audiences and channels and the transition towards real-time decisioning.
Own sub-projects where appropriate, leading junior colleagues and engaging with stakeholders.
Embody and improve best practice
Align to best practice across modelling, experimentation, deployment, and model lifecycle management.
Coach through doing – pairing on code and demonstrating standards.
Be an enthusiastic member of our community
Become the recognised data science technical expert in your team, bringing new ideas for future approaches, including state of the art techniques where appropriate.
Understand how our business really works, including by supporting our stores during peak trading periods.
Actively contribute to our vibrant Data and Analytics community of over 800 colleagues, providing a view on new techniques and approaches that can drive positive change in wider teams.
Who you are
We’re looking for a highly motivated self-starter – someone who fixes problems and creates value without micromanagement. You need to thrive in a challenging role, and know how to balance our need for technical rigour against our need to deliver commercial and customer value.
Value delivery
Deep experience in Data Science roles, with evidence of solving complex problems end-to-end.
A record of building systems which run in production, and an understanding of the value these generated.
An ability to understand commercial reality as well as technical rigour.
Experience working in an Agile way, and ability to understand the trade-off between immediate value, future value, and technical rigour.
A strong ability to communicate ideas to audiences of varying technical background and seniority.
Data Science expertise
Strong grounding in statistical modelling and machine learning, such as Predictive modelling at scale, unsupervised learning, causal inference and experimentation and optimisation and decisioning
Strong understanding of the “how” behind the algorithm; ability to select the right technique for a given objective and avoid pitfalls.
Production-grade design
Extensive programming ability across Python and strong ability to use SQL, with a proven experience of developing complex solutions in a corporate environment.
Solid understanding of working with production codebases, such as version control, CI/CD, and batch processing.
Practical experience working on cloud-based ML platforms.
Development and coaching
A strong awareness and understanding of technology trends and direction in Data Science, analytics and AI.
Ability to support in the development, training and mentoring of others.
Essential Criteria
Extensive experience in previous Data Science roles
A record of building systems which run in production
A strong ability to communicate ideas to audiences of varying technical background and seniority
Strong grounding in statistical modelling and machine learning, including predictive modelling and linear optimisation.
Extensive programming ability across Python and strong ability to use SQL
Solid understanding of working with production codebases, such as version control and CI/CD
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