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Senior Data Science Manager x2

Employer
Lloyds Banking Group
Location
London
Salary
£60600 - £94600 per annum + GoodPackage
Closing date
4 Feb 2021

Job Details

Senior Data Science Manager x2 (within Applied Sciences & Retail Transformation)

London or Bristol (central)

Lloyds Banking Group

Salary & Benefits: £60,600 to £94,600 base salary (Depending on location), 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. Working for Lloyds is great!

Who are Lloyds Banking Group?

Lloyds Banking Group is the UK's leading bank with over 30m customers and its biggest digital bank, with over 13 million active online customers. We've placed an ambitious transformation programme and a multi-channel approach to banking at the heart of our strategy to be the best bank for customers, backed by significant investment in our platforms and people.


Why join the Data Science Team?

You'll work on a wide range of interesting projects with no shortage of work! We take ideas from the concept stage and work with our customers to understand how data science and machine learning can be applied.

You'll play a pivotal role in the development of solutions for a wide range of business areas.

You'll help rapidly transform our capabilities and be a key player in our further digitisation using latest emerging technologies and services.


What will I do as a Senior Manager within Data Science?

You'll focus on leading a multi-disciplinary team of 5 - 12 people to delivery and continuously improve data science initiatives. You will also get the opportunity to remain hands on, as much as you feel suitable.

You'll lead all stages of a project from working with the users to explore the problem statement, exploring our data assets, experimenting with different modelling approaches and developing systems powered by Machine Learning all within an iterative and Agile environment.

Support the team to develop experimental models and Machine Learning systems alongside our Data Engineers (who build the data pipelines and ensure quality) and in close collaboration with our users and business SMEs.


Your data science solutions 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 experienced managers who have relevant experience and are interested in those from diverse industry/field backgrounds. As a minimum to be considered we will be looking for;

Experience implementing and supporting Machine Learning systems including automating data validation, model training, model validation and model monitoring.

Experience managing data science teams. Coaching, mentoring and developing.

From a technical perspective we'll need you to have hands on experience of a relevant software engineering practices, the full software development lifecycle within an Agile Data Science function, ideally including data science best practice.

Technically, we'll want you to demonstrate knowledge of software engineering best practice and advanced statistical techniques, for example;

  • Python, pandas, functional programming and databases systems are of interest. Additionally experience of working in a DevOps / CICD environment and making extensive use of automation would be what we would like to see.

  • A good theoretical and applied knowledge of Statistical Modelling and/or Machine Learning techniques such as some (not all!) of the following: regression, clustering, attribution (econometrics / MMM), decision trees (CHAID, random forest, XGBoost), significance testing, machine learning (classification and regression models, Keras, Tensorflow).

A pragmatic, "keep it simple" attitude to your work and designs.

A strong communicator, as we have a lot of involvement with our customers who are both technical and non-technical.

This would be a great role if:

  • You have a genuine interest in Data Science.

  • You want to contribute towards senior leadership forums within data science.

  • You are customer focused and want to continuously improve our systems.


And how will we challenge you?

You'll have the opportunity to partner across our various businesses to understand and work their complex problems through to solutions. We are really lucky to have a continuous and interesting supply of work.

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

You'll work with some of the best Data Science developers in the bank as we look to build a thriving data science community, whether through opportunities to share knowledge through self-starting guilds or coaching.


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… 

Interested but have a questions before you apply? Not sure if the role or culture at Lloyds is right for you? Feel free to reach out to me via Linked In using this link: http://bit.ly/JBarratt or via internal e-mail, with any questions and I'll be happy to help.

 

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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