Senior Data Scientist

Senior Data Scientist - Behavioural Data Salary: £70,000-£80,000 Location: Fully remote, UK Working pattern: Permanent, with a monthly meetup in London Im working with an exciting early-stage technology business developing innovative ways to understand human behaviour through the way people interact with technology.

Using data generated through mobile interactions, touch, movement and other behavioural signals, the business is building technology that can identify patterns in human behaviour and better understand how people interact with digital products.

Theyre now looking to bring another Data Scientist into their team, with a particular focus on complex datasets, time-series analysis and predictive modelling. This is an opportunity to work on some genuinely interesting data problems, combining scientific research, machine learning and engineering to develop models that can be taken through to production.

What youll be doing

Exploring and analysing large-scale, complex datasets, including sensor, device and behavioural data. Developing machine learning models to identify patterns and extract meaningful insights from time-series data. Applying signal processing and statistical techniques to understand complex and potentially noisy datasets.

Building, testing and evaluating predictive models using Python. Taking models from initial research and experimentation through to production. Working closely with the wider Data Science and Engineering teams to develop and improve modelling approaches.

Exploring new techniques to understand human behaviour, interactions and patterns within digital environments. Theyre particularly interested in people who combine strong technical Data Science skills with a scientific or research-led background.

You'll ideally have

Strong Python skills and hands-on experience developing machine learning models. Experience working with time-series, sequential or high-frequency data. Exposure to sensor, device, physiological, motion or other signal-based datasets.

A good understanding of statistical modelling, signal processing or predictive analytics. Experience taking models beyond experimentation and into production environments. The ability to work with complex datasets and identify meaningful patterns.

A background in one of the following areas would be Ideal: Neuroscience or computational neuroscience. Signal processing or neurotechnology. Medical devices, wearables or physiological data. Computational biology or other quantitative scientific disciplines.

Research-led Machine Learning or applied Data Science. Experience working with mobile, gaming or other behavioural datasets would also be beneficial, but isnt essential...

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