Data Scientist

£65000 - £90000 per annum




The ideal candidate:

· Well versed at applying advanced analytical and AI techniques, particularly Natural Language Processing (NLP), to large datasets. Sample techniques include, but are not limited to:

o Aspect-Based Sentiment Analysis (ABSA)

o Multilingual NLP

o Entity recognition and linking

o Topic classification/modelling

o Document information extraction

o Document clustering

o NLP pipeline automation

· Experience with:

o Applying latest NLP techniques such as Transformers in production, with awareness of the challenges.

o Creating performance metrics and tracking processes to measure the effectiveness of Data Science solutions

o Conceptualizing necessary data governance models to support the technical solution and assure the integrity of the 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

o In-depth knowledge on at least one of the mainstream deep learning frameworks such as PyTorch, TensorFlow

o Understanding software development best practices

o At least one primary 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. participating 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 organization skills to work with a high-performance team, handle demanding clients and multitask effectively and in an agile way


· 3+ years of Experience in AI, data science, data engineering and/or other technology-related capabilities in multiple industries. Experience in the 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:

o Proficient with programming languages used by data scientists like Python, R, Scala

o Experience with Linux, git, docker

o Software Engineering best practices and Object-Oriented Programming

o Skills in data engineering technologies like Hadoop, HDFS, Spark, Elasticsearch

o SQL and NoSQL databases

o Cloud certification is a plus or willingness to work towards one of the following:

§ GCP – Machine Learning Engineering

§ GCP – Data Engineering

§ Azure – Data Scientist

§ Azure – AI Engineering

§ Azure – Data Engineering

§ AWS – Machine Learning Specialty


McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.


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