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Experienced Professional

Lead DevOps Engineer

Location: Leeds

Service Line: Solutions & Digital

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Experienced Professional

Data Scientist - Assistant Manager

Location: London

Service Line: Solutions & Digital

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Experienced Professional

Lead DevOps Engineer - Cloud Engineering

Location: London

Service Line: Solutions & Digital

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Experienced Professional

Lead Data Scientist - Senior Manager

Location: London

Service Line: Solutions & Digital

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Experienced Professional

Senior Data Scientist - Manager

Location: London

Service Line: Solutions & Digital

View role

Lead DevOps Engineer

Location: Leeds

Capability: Solutions & Digital

Service line: Solutions & Digital

Experience level: C

Employment type: Full Time


The Team

Within KPMG's Technology & Engineering team, the Cloud Engineering mission is to be the best cloud team ever by doing the right thing, using the right tools, failing fast and automating like our lives depend on it.

We operate at genuine scale partnering the big three public cloud providers and have our own private cloud to deliver cutting edge solutions to clients on a global stage. If the public cloud is your future and you’re amazing at solving difficult, interesting and complex challenges and actually writing code, roll up your sleeves then drop us a line and remember to bring cake when you meet us.


You will be working to continuously advance and standardise our clients infrastructure and deployments, whilst collaborating with colleagues to write infrastructure as code that scales and takes advantage of the technologies used.

The Role

• Help design and build monitoring systems, metrics, internal dashboards, and other tools that allow KPMG clients to become increasingly, scalable, and reliable infrastructure.
• Continue to cultivate a culture of collaboration, innovation and bringing industry standards to everything we do.
• You understand the fundamentals: Cloud Technologies (AWS, Azure, Private), Windows, Linux, Security and Networking.
• An ability to automate processes.


The Person

• Cloud Technologies exposure (AWS, Azure, Private), Windows, Linux, Security and Networking.
• You will have used the following - Python, Nodejs, C#, Cloudformation Templating, Ansible / Salt, Octopus, Team City / Jenkins
• You have experience building highly scalable, secure, efficient, and resilient systems.
• Ability to continuously learn, work independently, and make decisions with minimal supervision.
• You like nothing more than to watch colleagues flourish under your guidance.
• You love steering a very willing team to increase performance and efficiency.
• Be a technological cloud advocate to a wider audience inside and outside of the business.


What we can offer
• Scale, some of our clients are well known global brands, their infrastructure isn't small.
• A great team environment, inside and outside of the work place.
• Love of technology and learning about even newer technology to help our clients be successful.
• Flexible and considerate working hours.
• Access to regular training opportunities and certification which can include Internal, AWS and Pluralsight.
• Generous pay and benefits such as a subsidised lunch, health care, pension, cycle to work, free day off to celebrate your birthday.
• Excellent relationship with vendors and access to authorities within their field.



Data Scientist - Assistant Manager

Location: London

Capability: Solutions & Digital

Service line: Solutions & Digital

Experience level: D

Employment type: Full Time



The Team

Many of our clients are on a ‘digital transformation journey’ to increase profits whilst reducing reputational, operational, financial and other risks. Our highly specialised Data Science and Engineering team in our KPMG ‘Lighthouse’ uses advanced analytical techniques and industrial scale technology platforms to help our clients accelerate their digital transformation journeys. Typical projects require extracting a variety of data at large scale, drawing deep insights using complex analytical algorithms, and visualising the results to articulate compelling and engaging stories that, in the end, deliver increased value from that data. Our UK team works closely together with data science and engineering teams around the world, supported by our global ‘Ignite platform’, in order to maximise our collective success


The Role
• At KPMG, our values define who we are and the way we do business. As a leading professional services firm, we know that our strength and capability come from our people – their different perspectives, experiences and backgrounds. From our inclusive leadership strategy to our diversity and inclusion targets – we’re making bold changes to who we are and what we do. Be part of it.
• Our Data Scientists support the whole firm on a wide variety of projects, across our Audit, Tax and Advisory business. We are experienced in managing diverse issues including business disruption, process optimisation, resource optimisation, fraud, regulatory compliance, dispute resolution, deriving value from contracts and much more
• Client related work: A Data Scientist would typically work under the guidance of a Senior Data Scientist and collaboratively with our business teams and our clients to show the art of the possible and to assess possible value and feasibility of applying data science in order to help solve specific business problems. This could include demoing to prospective clients, developing data strategies, leading feasibility studies, explorative data analysis, delivering minimal viable products or fully fledged projects including putting our models into production either on our own or our client’s environments.
• Asset development: Build data science assets (aka ‘accelerators’), in line with our UK and/or global strategy, to ensure we have the platforms and core assets in place to meet market demand. This could also include supporting our continuous improvement process around our own design and development processes e.g. about how we ensure the high quality that our clients require in an efficient manner.
• People: As a fast growing highly specialised team, several of team members will be involved in the running and growing of our team, e.g. through involvement in hiring and coaching colleagues, helping with knowledge management, organising team meetings or other events.

Roles & Responsibilities

• Operate as part of a team of Data Scientists on specific engagements, focused on the development, training and monitoring of data science solutions that accelerate our clients’ digital journeys.
• Work collaboratively with our business teams and our clients to develop solutions that solve business problems
• Support client engagements focused on large data sets and applying advanced analytical techniques, in diverse domains such as retail price optimisation, channel management, marketing strategies, customer intelligence, financial crime, risk management, healthcare digitisation, smart grids, etc.
• Monitor performance to ensure models perform as effectively as possible.
• Develop new, or tailor existing, analytical solutions designed for processing large data sets (e.g. using an Hadoop framework) and by applying advanced analytical techniques (e.g. machine learning, neural networks, NLP, A/B testing, etc.)
• Liaise with our advanced Data Engineers in terms of data engineering, model deployment and architecture activities to jointly build solutions that will interoperate seamlessly with other elements of the broader information architecture

The Person
• Well versed at applying advanced analytical techniques to large and varied data sets, generated and flowing at a rapid rate. Sample techniques include, but are not limited to:
o Applied machine learning
o Natural language processing
o Collaborative filtering and recommender systems
o Neural networks (including recurrent, convolutional)
o Event detection and tracking
o Graph Analytics

• Experience with:
o Analysing data growth and lead capacity/sizing activities to arrive at the most appropriate commercial and technical solution
o Generating and test working hypotheses, prepare and analyse historical data, identify patterns from samples for reporting of trends and support Predictive Analytics
o Leveraging data visualisation techniques and tools to effectively demonstrate patterns, outliers and exceptional conditions in the data
o Creating performance metrics and tracking processes to measure the effectiveness of Data Science solutions
o Deploying models into production, with awareness of the challenges.
o Conceptualising necessary data governance models to support the technical solution and assure the veracity of the data
o Operating within the exploratory and experimental aspects of Data Science, e.g. to tease out interesting and previously unknown insights from vast pools of data
o Working collaboratively with other members of the Data Science and Information Architecture teams to innovate and create compelling data-centric stories and experiences
o Proficient with programming languages used by data scientists and in big data platforms, like Python, R, Scala, Julia, Java.
• Track record in staying conversant in new analytic technologies, architectures and languages – where necessary – for storing, processing and manipulating this type of data
• Demonstrated Data Science consultancy skills, e.g. participate in hypotheses workshops, mentoring more junior team members, preparing reports and presenting data science results.
• Skilled to communicate with a variety of stakeholders in the organization
• Planning and organisation skills so as to work with a high performance team, handle demanding clients and multitask effectively

Qualifications
• Experience in data, data science, data engineering and/or other technology related capabilities
• BSc (ideally MSc) in Computer Science, Statistics, Engineering or similar technical field
• A combination of one or more of the following:
o Proficient with programming languages used by data scientists like Python, R, Scala, Julia, Java, C++
o Skills in data engineering technologies like Hadoop, HDFS, Spark, Elasticsearch
o SQL and NoSQL databases


Lead DevOps Engineer - Cloud Engineering

Location: London

Capability: Solutions & Digital

Service line: Solutions & Digital

Experience level: C

Employment type: Full Time


The Team

The Cloud Engineering mission is to be the best cloud team ever by doing the right thing, using the right tools, failing fast and automating like our lives depend on it.

We operate at genuine scale partnering the big three public cloud providers and have our own private cloud to deliver cutting edge solutions to clients on a global stage. If the public cloud is your future and you’re amazing at solving difficult, interesting and complex challenges and actually writing code, roll up your sleeves then drop us a line and remember to bring cake when you meet us.


You will be working to continuously advance and standardise our clients infrastructure and deployments, whilst collaborating with colleagues to write infrastructure as code that scales and takes advantage of the technologies used.

The Role

• Help design and build monitoring systems, metrics, internal dashboards, and other tools that allow KPMG clients to become increasingly, scalable, and reliable infrastructure.
• Continue to cultivate a culture of collaboration, innovation and bringing industry standards to everything we do.
• You understand the fundamentals: Cloud Technologies (AWS, Azure, Private), Windows, Linux, Security and Networking.
• An ability to automate processes.


The Person

• Cloud Technologies exposure (AWS, Azure, Private), Windows, Linux, Security and Networking.
• You will have used the following - Python, Nodejs, C#, Cloudformation Templating, Ansible / Salt, Octopus, Team City / Jenkins
• You have experience building highly scalable, secure, efficient, and resilient systems.
• Ability to continuously learn, work independently, and make decisions with minimal supervision.
• You like nothing more than to watch colleagues flourish under your guidance.
• You love steering a very willing team to increase performance and efficiency.
• Be a technological cloud advocate to a wider audience inside and outside of the business.


What we can offer
• Scale, some of our clients are well known global brands, their infrastructure isn't small.
• A great team environment, inside and outside of the work place.
• Love of technology and learning about even newer technology to help our clients be successful.
• Flexible and considerate working hours.
• Access to regular training opportunities and certification which can include Internal, AWS and Pluralsight.
• Generous pay and benefits such as a subsidised lunch, health care, pension, cycle to work, free day off to celebrate your birthday.
• Excellent relationship with vendors and access to authorities within their field.



Lead Data Scientist - Senior Manager

Location: London

Capability: Solutions & Digital

Service line: Solutions & Digital

Experience level: B

Employment type: Full Time



The Team

Many of our clients are on a ‘digital transformation journey’ to increase profits whilst reducing reputational, operational, financial and other risks. Our highly specialised Data Science and Engineering team in our KPMG ‘Lighthouse’ uses advanced analytical techniques and industrial scale technology platforms to help our clients accelerate their digital transformation journeys. Typical projects require extracting a variety of data at large scale, drawing deep insights using complex analytical algorithms, and visualising the results to articulate compelling and engaging stories that, in the end, deliver increased value from that data. Our UK team works closely together with data science and engineering teams around the world, supported by our global ‘Ignite platform’, in order to maximise our collective success


• At KPMG, our values define who we are and the way we do business. As a leading professional services firm, we know that our strength and capability come from our people – their different perspectives, experiences and backgrounds. From our inclusive leadership strategy to our diversity and inclusion targets – we’re making bold changes to who we are and what we do. Be part of it.
• Our Data Scientists support the whole firm on a wide variety of projects, across our Audit, Tax and Advisory business. We are experienced in managing diverse issues including business disruption, process optimisation, resource optimisation, fraud, regulatory compliance, dispute resolution, deriving value from contracts and much more
• Strategy: Lead strategic data science developments across the organisation
• Client related work: A Lead Data Scientist would typically work collaboratively with our business teams and our clients to show the art of the possible and to assess possible value and feasibility of applying data science in order to help solve specific business problems. This could include demoing to prospective clients, developing data strategies, leading feasibility studies, explorative data analysis, delivering minimal viable products or fully fledged projects including putting our models into production either on our own or our client’s environments.
• Asset development: Build data science assets (aka ‘accelerators’), in line with our UK and/or global strategy, to ensure we have the platforms and core assets in place to meet market demand. This could also include supporting our continuous improvement process around our own design and development processes e.g. about how we ensure the high quality that our clients require in an efficient manner.

Roles & Responsibilities

• Lead a team of Data Scientists, focused on the development, training and monitoring of data science solutions that accelerate our clients’ digital journeys.
• Drive client engagements focused on large data sets and applying advanced analytical techniques, in diverse domains such as retail price optimisation, channel management, marketing strategies, customer intelligence, financial crime, risk management, healthcare digitisation, smart grids, etc.
• Monitor performance to ensure models perform as effectively as possible.
• Develop new, or tailor existing, analytical solutions designed for processing large data sets (e.g. using an Hadoop framework) and by applying advanced analytical techniques (e.g. machine learning, neural networks, NLP, A/B testing, etc.)
• Liaise with our advanced Data Engineers in terms of data engineering, model deployment and architecture activities to jointly build solutions that will interoperate seamlessly with other elements of the broader information architecture

The Person
• Well versed at applying advanced analytical techniques to large and varied data sets, generated and flowing at a rapid rate. Sample techniques include, but are not limited to:
o Applied machine learning
o Natural language processing
o Collaborative filtering and recommender systems
o Neural networks (including recurrent, convolutional)
o Event detection and tracking
o Graph Analytics

• Experience with:
o Generating and test working hypotheses, prepare and analyse historical data, identify patterns from samples for reporting of trends and support Predictive Analytics
o Leveraging data visualisation techniques and tools to effectively demonstrate patterns, outliers and exceptional conditions in the data
o Creating performance metrics and tracking processes to measure the effectiveness of Data Science solutions
o Conceptualising necessary data governance models to support the technical solution and assure the veracity of the data
o Operating within the exploratory and experimental aspects of Data Science, e.g. to tease out interesting and previously unknown insights from vast pools of data
o Working collaboratively with other members of the Data Science and Information Architecture teams to innovate and create compelling data-centric stories and experiences
o Proficient with programming languages used by data scientists and in Big Data platforms, like Python, R, Scala, Spark, Julia, Java.
• Track record in staying conversant in new analytic technologies, architectures and languages – where necessary – for storing, processing and manipulating this type of data
• Demonstrated Data Science leadership skills, e.g. around establishing or growing Data Science teams through recruiting talented individuals, training colleagues, writing proposals and designing and delivering high value propositions
• Persuasive power to communicate with a variety of stakeholders in the organization
• Working with Market Segment Leaders and their account teams, to identify strategic client issues, shape deals which demonstrate business value and work hands-on to lead engagements which leverage AI to solve business problems
• Assist in the full sales cycle, taking a leadership role in the creation of new highly differentiated solutions
• Planning and organisation skills so as to work with a high performance team, handle demanding clients and multitask effectively
Proven skill in working with all stakeholders (internal and external) on a project
Qualifications
• Experience in data, data science, data engineering and/or other technology related capabilities
• Ph.D. in Computer Science, Machine Learning, Statistics, Engineering or similar technical field
• A combination of one or more of the following:
o Proficient with programming languages used by data scientists like Python, R, Scala, Julia, Java, C++
o Skills in data engineering technologies like Hadoop, HDFS, Spark, Elasticsearch

We recognise that as individuals, we each have particular needs and that one size doesn’t fit all, when it comes to how, when and where you work. That’s why we’re proud to offer our colleagues agile working options. We believe in putting you at the centre of your career – KPMG will offer the training, development and stimulating work environment to help you get to where your career ambitions are. That’s why we introduced ‘Our Deal’ – it’s our way of saying ‘thank you’ for bringing your best to work. As part of ‘Our Deal’, you’ll benefit from a range of rewards from secondment opportunities and preferential banking services to a day off on your birthday and have open, honest conversations about your career development.

Senior Data Scientist - Manager

Location: London

Capability: Solutions & Digital

Service line: Solutions & Digital

Experience level: C

Employment type: Full Time



The Team

Many of our clients are on a ‘digital transformation journey’ to increase profits whilst reducing reputational, operational, financial and other risks. Our highly specialised Data Science and Engineering team in our KPMG ‘Lighthouse’ uses advanced analytical techniques and industrial scale technology platforms to help our clients accelerate their digital transformation journeys. Typical projects require extracting a variety of data at large scale, drawing deep insights using complex analytical algorithms, and visualising the results to articulate compelling and engaging stories that, in the end, deliver increased value from that data. Our UK team works closely together with data science and engineering teams around the world, supported by our global ‘Ignite platform’, in order to maximise our collective success


The Role
• At KPMG, our values define who we are and the way we do business. As a leading professional services firm, we know that our strength and capability come from our people – their different perspectives, experiences and backgrounds. From our inclusive leadership strategy to our diversity and inclusion targets – we’re making bold changes to who we are and what we do. Be part of it.
• Our Data Scientists support the whole firm on a wide variety of projects, across our Audit, Tax and Advisory business. We are experienced in managing diverse issues including business disruption, process optimisation, resource optimisation, fraud, regulatory compliance, dispute resolution, deriving value from contracts and much more
• Client related work: A Senior Data Scientist would typically work works collaboratively with our business teams and our clients to show the art of the possible and to assess possible value and feasibility of applying data science in order to help solve specific business problems. This could include demoing to prospective clients, developing data strategies, leading feasibility studies, explorative data analysis, delivering minimal viable products or fully fledged projects including putting our models into production either on our own or our client’s environments.
• Asset development: Build data science assets (aka ‘accelerators’), in line with our UK and/or global strategy, to ensure we have the platforms and core assets in place to meet market demand. This could also include supporting our continuous improvement process around our own design and development processes e.g. about how we ensure the high quality that our clients require in an efficient manner.
• People: As a fast growing highly specialised team, you will be involved in the running and growing of our team, e.g. through involvement in hiring and coaching colleagues, helping with knowledge management, organising team meetings or other events.

Roles & Responsibilities

• Manage a team of Data Scientists on specific engagements, focused on the development, training and monitoring of data science solutions that accelerate our clients’ digital journeys.
• Work collaboratively with our business teams and our clients to develop solutions that solve business problems
• Support client engagements focused on large data sets and applying advanced analytical techniques, in diverse domains such as retail price optimisation, channel management, marketing strategies, customer intelligence, financial crime, risk management, healthcare digitisation, smart grids, etc.
• Monitor performance to ensure models perform as effectively as possible.
• Develop new, or tailor existing, analytical solutions designed for processing large data sets (e.g. using an Hadoop framework) and by applying advanced analytical techniques (e.g. machine learning, neural networks, NLP, A/B testing, etc.)
• Liaise with our advanced Data Engineers in terms of data engineering, model deployment and architecture activities to jointly build solutions that will interoperate seamlessly with other elements of the broader information architecture

The Person
• Well versed at applying advanced analytical techniques to large and varied data sets, generated and flowing at a rapid rate. Sample techniques include, but are not limited to:
o Applied machine learning
o Natural language processing
o Collaborative filtering and recommender systems
o Neural networks (including recurrent, convolutional)
o Event detection and tracking
o Graph Analytics
• Experience with:
o Generating and test working hypotheses, prepare and analyse historical data, identify patterns from samples for reporting of trends and support Predictive Analytics
o Leveraging data visualisation techniques and tools to effectively demonstrate patterns, outliers and exceptional conditions in the data
o Creating performance metrics and tracking processes to measure the effectiveness of Data Science solutions
o Conceptualising necessary data governance models to support the technical solution and assure the veracity of the data
o Operating within the exploratory and experimental aspects of Data Science, e.g. to tease out interesting and previously unknown insights from vast pools of data
o Working collaboratively with other members of the Data Science and Information Architecture teams to innovate and create compelling data-centric stories and experiences
o Proficient with programming languages used by data scientists and in Big Data platforms, like Python, R, Scala, Spark, Julia, Java.
• Track record in staying conversant in new analytic technologies, architectures and languages – where necessary – for storing, processing and manipulating this type of data
• Demonstrated Data Science consultancy skills, e.g. running hypotheses workshops, mentoring more junior team members, preparing reports and presenting data science results.
• Skilled to communicate with a variety of stakeholders in the organization
• Planning and organisation skills so as to work with a high performance team, handle demanding clients and multitask effectively

Qualifications
• Experience in data, data science, data engineering and/or other technology related capabilities
• Ph.D. in Computer Science, Statistics, Engineering or similar technical field
• A combination of one or more of the following:
o Proficient with programming languages used by data scientists like Python, R, Scala, Julia, Java, C++
o Skills in data engineering technologies like Hadoop, HDFS, Spark, Elasticsearch
o SQL and NoSQL databases

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