Machine Learning Data Scientist

Job Category:
Job Type:
Level of IT Experience:
5-10 Years
North Ireland
Salary Description:
Competitive salary offered
Job Ref:

Data Scientist - Leading data science research lab, developing research grade, bespoke software in a wold renown environment

£40,000 - £70,000 + fantastic benefits package including flexible working, unlimited holiday scheme, generous pension, share scheme/equity opportunities and more.

London - Central

Organisation Overview:

Are you looking for the ultimate data science position which gives you the opportunity to work on cutting edge, bespoke and flagship data science, machine learning and artificial intelligence projects?

We are recruiting for a well-known and highly regarded organisation in the field of research-grade, enterprise wide machine learning, artificial intelligence and data science software and platforms. Their research labs are at the forefront of machine learning and computer science working with Harvard, UCL and other leading universities to push the endless possibilities of AI, ML and DS. They have also developed a world-leading platform, giving you access to some of the most sophisticated and powerful computational resources available.

Your role:

As a data scientist you will work with project teams to deliver bespoke algorithms, data science products, machine learning capabilities and artificial intelligence use cases to clients. You will normally work as part of a team to build, develop and deploy data pipelines, Machine learning capabilities and advanced models within a commercial engagement.

You will also actively contribute to the growth of the company reputation in Data science communities through thought leadership, including contributing to large-scale open-source projects. We are looking for people who take initiative. You will receive more responsibility from day one than you would expect in comparable roles elsewhere. You will take pride in:

* Solving problems with the best data-science techniques and in the most scientifically robust fashion

* Communicating technical content at the right level both internally and to clients

* Fostering a collaborative work environment, sharing knowledge, and bringing the best out of everyone in the team

* Seeking out innovative ways to make the company grow, for example, by turning project work into reusable code

About You:

* Experience in either a professional data science position or a quantitative academic field

* Prior research experience (PhD or Postdoc) as evidenced by academic publications and conference talks

* Strong programming skills as evidenced by earlier work in data science or software engineering. (e.g. Python, R, C, MATLAB)

* An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe)

* A high level of mathematical competence and proficiency in statistics

* A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models.

* We regard the ability to develop new algorithms when an innovative solution is needed as a fundamental skill

* An appreciation for the scientific method as applied to the commercial world

In addition to the above, we'd love it if you had:

Some knowledge of:

* Probabilistic programming languages such as Stan, PyMC3, Edward or Greta

* Distributed-computing frameworks such as Spark and Dask

* Utilities for the creation of web apps such as Flask, Dash and React.js

* Contributions to open-source projects

* Commercial experience, particularly if this involved client-facing work or project management


To ensure you don't miss out on this incredible opportunity, please apply as soon as possible to Michael Tyrrell - Harvey Nash Data Science Practice, by submitting your CV and any other relevant material

Contact Details:
Contact: Contact

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