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Retail Senior Data Scientist / Retail Data Science Manager

Employer
Lloyds Banking Group
Location
London
Salary
£68,139 - £75,710 per annum
Closing date
20 May 2021

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Job Details

Retail Senior Data Scientist / Retail Data Science Manager

Lloyds Banking Group

Location: London

Salary & Benefits: £68,000 to £79,495 base salary, plus annual personal bonus, 15% employer pension contribution (when you put in 6%), 4% flexible cash pot, private medical insurance, 30 days holiday plus bank holidays. We also offer flexible working hours, agile working practices and regular home working.


Why join the Retail Data Science Team?

An exciting opportunity to join a new and growing team, playing a critical role in the operation, development & release of data science models across Retail division.

You'll work across multiple projects and work with our business stakeholders to understand how we can best apply data science to deliver value.

You'll gain insight into the data & analytics agenda of the Retail division whilst contributing directly to it and will play a pivotal role in realising our digital and data potential and creating the Bank of the Future.


What will I do as a Data Scientist within the Retail Data Science team?

You will support the operation, maintenance and development of a range of Retail data science models - continuously looking to identify and implement improvements and meet business requirements.

You will work on models and Machine Learning systems in Python alongside our data engineers (who build the data pipelines and ensure quality) and in close collaboration with the end users and business SMEs

The role will evolve as the team continues to mature - and we're looking for someone who is highly driven, keen to learn and adopt new ways of working and can apply themselves across a wide range of responsibilities


Your work will have a material impact on the lives of up to 30m+ customers across the whole of the UK - and together we'll make it possible …


Are you who we're looking for?

We're keen to speak to Data Scientists that have at least 4 years of experience in delivering Data Science in Python for large scale industry applications.

A strong theoretical and applied knowledge of Statistical Modelling and/or Machine Learning techniques is required such as: regression, clustering, attribution (econometrics / MMM), decision trees (CHAID, random forest, XGBoost) and significance testing.

A good understanding of Python and SQL is also required including how to write modular Pythonic code, familiarity with the core Python data structures and fluency with pandas; a familiarity with unit testing would be beneficial.

The ability to present the learnings from these techniques in a clear, visual manner to support senior stakeholder decision making is key

Experience implementing and supporting Machine Learning systems including automating data validation, model training, model validation and model monitoring would also be very useful.


And how will we challenge you?

You'll have the opportunity to contribute as we shape our team. You will work across multiple business domains, developing strong stakeholder relationships and working complex problems through to solutions.

You'll get exposure to a host of wider technologies and career moves at LBG by broadening your horizons and giving you opportunities to stretch yourself.

You'll work with some of the best Data Scientists in the bank as we look to build a thriving data science community, whether through opportunities to share knowledge through self-starting guilds or coach other junior data scientists to support their career development.


What you'd get in return:
Offering you both funding and profile - we'll provide you with a diverse, energising and informal environment that focuses on equal opportunity and real career progression.


We'll take your personal and professional development very seriously and enable you to make a difference to millions throughout your career with us.

Together we'll make it possible… 

Company

We’re creating an organisation that attracts, retains and develops the best talent in the industry, and one that openly embraces diversity too. But more than that – we want to be a great place to work. We invest in our people, offering the best training and coaching, and by encouraging them to contribute to our leading corporate and social responsibility practices. We offer flexible working hours and days, under our Work Options scheme. This means that you can have a challenging and rewarding career, and still have an ideal work/life balance.

Flexible working is at the heart of our strategy. We’re re-imagining where, when, and how our people work, with new approaches designed to meet the ever-changing needs of customers and colleagues. These include increasing our use of remote-working tools and technology, as well as placing less reliance on a 9-to-5 mindset. For many of our office-based colleagues, we work in hybrid ways which involves spending at least two days per week or 40% of their time at one of our office sites.

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