KPMG Hiring for NLP Research Engineer Job at London, England Full Time

Job details

Location: London, Manchester

Capability: Consulting

Experience Level: Associate/Assistant Manager

Type: Full Time

Service Line: Tech Digital Lighthouse

Contract type: Permanent

Job description

Assistant Manager – NLP Research Engineer (D grade)

Roles & Responsibilities

• Client Project Delivery: An Assistant Manager/Data Scientist would typically work as part of a team on specific engagements or workstreams, focused on developing new, or tailoring existing, AI solutions designed for processing large data sets (e.g., using a Hadoop framework) that accelerate our clients’ digital journeys. This could include creating Proof of Concept, delivering minimal viable products or fully fledged projects including putting our models into production either on our own or our client’s environments.
• Business Development: 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 to help solve specific business problems. This could include demoing to prospective clients, conducting feasibility studies, and supporting RFP responses.
• 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.

• Collaboration: Liaise with our advanced data engineering and cloud engineering team for architecture design and model deployment to jointly build solutions and products that will interoperate seamlessly with other elements of the broader information architecture

• 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.

The Person

• Well versed at applying advanced analytical and AI techniques, in particular Natural Language Processing (NLP), to large datasets. Sample techniques include, but are not limited to:
  • Aspect-Based Sentiment Analysis (ABSA)
  • Multilingual NLP
  • Entity recognition and linking
  • Topic classification/modelling
  • Document information extraction
  • Document clustering
  • NLP pipeline automation
• Experience with:
  • Applying latest NLP techniques such as Transformers in production, with awareness of the challenges.
  • Creating performance metrics and tracking processes to measure the effectiveness of Data Science solutions
  • Conceptualising necessary data governance models to support the technical solution and assure the veracity of the data
  • Working collaboratively with other members of the Data Science and Information Architecture teams to innovate and create compelling data-centric stories and experiences
  • Proficient with programming languages used by data scientists and in Big Data platforms, like Python, R, Scala
  • In-depth knowledge on at least one of the mainstream deep learning frameworks such as PyTorch, TensorFlow
  • Understanding software development best practices
  • At least one major cloud provider (AWS, GCP, Azure), their machine learning and engineering services. GCP experience is preferred.
• 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 and in an agile way

Qualifications

• 3+ years of experience in AI, data science, data engineering and/or other technology related capabilities in one or multiple industries. Experience in Financial Service sector, in particular ESG analytics and risk management, is preferred.
• BSc (ideally MSc or PhD) in Computer Science, Statistics, Engineering or similar technical field
• A combination of one or more of the following:
  • Proficient with programming languages used by data scientists like Python, R, Scala
  • Experience with Linux, git, docker
  • Software Engineering best practices and Object-Oriented Programming
  • Skills in data engineering technologies like Hadoop, HDFS, Spark, Elasticsearch
  • SQL and NoSQL databases
  • Cloud certification is a plus or willingness to work towards one of the followings:
    • GCP – Machine Learning Engineering
    • GCP – Data Engineering
    • Azure – Data Scientist
    • Azure – AI Engineering
    • Azure – Data Engineering
    • AWS – Machine Learning Specialty

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.

While our people can be required to travel, and at times be based at client sites, our flexible working arrangements can help you to achieve a balanced lifestyle. We offer part time roles with flexible working arrangements which could include, annualised hours, early or late starts to fit around other commitments, shorter working days etc. We are happy to discuss your own requirements and our range of flexible working arrangements in more detail, should that be of interest and, as part of the recruitment process, we can put you in touch with people who work flexibly.

Job Segment: Data Science, Artificial Intelligence, AI, Analytics, Data Analytics, Senior Manager, Data Scientist

Why Consulting at KPMG?

Technology is a critical focus for us. It underpins everything we do. We’re investing in technology like never before – not least because the pace of technological change is disrupting organisations in new and challenging ways. Through advanced data analytics and emerging tech-enabled solutions like AI and machine learning, we’re helping clients across diverse sectors to navigate that change. We enable them to avoid any unnecessary risks and to uncover new, transformative opportunities that could give them a competitive edge. A career here means stretching your skills and honing your expertise by solving complex problems as part of a collaborative, results-driven and supportive team. Whether we’re helping our clients to reduce their costs, make better decisions, improve efficiencies or deploy the latest technologies, we bring together broad specialisms and talents to deliver robust, connected solutions.