Machine Learning Engineer (data scientist)

  • Permanent
  • London
  • data science
  • excellent salary, bonus, full bens
  • 3335ML

Machine Learning Engineer, Python, Machine Learning, Data Scientist

Work from home, Remote delivery, UK based.  Leading Blue Chip customer – excellent package, bonus, full bens, home working 

Experienced Machine Learning Engineer with solid Python experience and ideally consumer products, online recommendations experience.

The Machine Learning Engineer role:

  • make appropriate use of Machine Learning techniques to build models that can be used to transform the online experience into a more personalised one.
  • apply software engineering best practice to your day-to-day work, ensuring that the technical debt you accumulate through experimentation is regularly repaid with robust solutions that are modular, extensible, well tested and easily moved into production.
  • data manipulation, so be comfortable with regexes and command line tools.
  • machine learning life cycle and MLOps, taking a holistic view of the model deployment when developing the model
  • help Data Engineers build the data pipelines required for productionised ML models to train and run at scale in the cloud.
  • work with Product Owners to suggest ways in which personalisation, relevancy/timeliness of recommendations and website conversion can be improved.
  • understand A/B and multi-armed bandit tests, and have a good grasp of basic statistics concepts.
  • guide and mentor our client in IT and Insight functions who are interested in learning more about data science and machine learning.
  • support the development of the wider data science and machine learning community.
  • be aware of the biases that may be introduced into data sets and models and guard against them

Essential:

  • Solid Python programming with relevant packages for statistics, machine learning and numerical computing, eg numpy, scipy, scikit-learn, tensorflow, keras.
  • Git version control, unit testing, continuous integration and best practices
  • Delivery of models and data pipelines in a repeatable, reliable, automatable fashion
  • Manipulate data and rapidly prototype and communicate solutions in Jupyter notebooks.
  • Transform prototype solutions into something modular, extensible, tested and production ready.
  • Produce and deploy machine-learning models on cloud-based infrastructure, containerisation and data pipelines.
  • Understanding of classical statistics and its applications particularly to hypothesis testing and inference.
  • Strong modern machine learning techniques, particularly neural networks, Word2Vec, and representation learning.
  • Experience with recommendations systems.
  • Not afraid to read research papers, adapt and apply ideas from the latest research.
  • Able to visualise and communicate results in a compelling way to people who may be new to machine learning
  • Work with other data scientists, engineers, product owners, business analysts and delivery leads

Desirable:

  • Google Cloud Platform.
  • agile software development team.
  • common data engineering technologies
  • Bayesian statistics

#machinelearning #datascientist #pythonjobs #recommendations #numpy #scipy #scikitlearn #tensorflow #keras

This advert was posted by Staffworx Limited – a UK based recruitment consultancy supporting the global digital, E-commerce, software & consulting sectors. Services advertised by Staffworx are those of an Agency and/or an Employment Business.

Staffworx operate a referral scheme of £500 or new iPad for each successfully referred candidate, if you know of someone suitable please forward for consideration.

 

 

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