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Senior Data Scientist - Deep Learning for Energy Forecasting, England, UK, London

Job Type:
Permanent
Job Sector:
Data, Technology
Job Category:
Data Science & Data Engineering
Country:
UK
Area:
London
Location:
England
Salary:
70,000 to 100,000 per annum
Job Ref:
HQ00025105

Senior Data Scientist Energy Demand Forecasting with Deep Learning

Xcede's Data Science & Engineering team are working with a hugely exciting start-up in London who are disrupting the way the energy industry works. By providing an automated model for understanding energy consumption on more regular intervals (based on recent changes in UK regulations), the company in question are providing a more affordable, and cleaner service for their customers. While the business model is relatively straight forward, the tech behind it is anything but.

If you're interested in using Deep Learning (RNNs / LSTMs) methods in an applied setting, this could well be the job for you. With a 3-person team of ex-academics in place (coming from backgrounds focusing on reinforcement learning, deep learning, etc.) we're currently looking for a "hands-on" senior data scientist / lead data scientist to help guide them in a commercial setting.

Key Responsibilities:

- Design, implement, & optimise Deep Learning algorithms for the company's core product.
- Mentor Junior & Mid-Level Data Scientists
- Make more Data Science hires & take part in interviews
- Help work on company strategy from a data driven perspective.

Requirements:

- MSc / PhD background in a related Comp Sci / AI / ML related area.
- Commercial experience in an applied ML / DL setting
- Ideally Recurrent Neural Network experience (RNN / LSTMs)
- Some proof of mentoring ideally
- Python, TensorFlow, Spark, AWS (we're pretty flexible though it's all about the right tool for the right job!)


If you are interested in this or other Data Scientist or Data Engineer positions, please contact Niall Wharton on niall.wharton@xcede.co.uk or +44(0)203 301 9908

Contact Details:
Tel: 0203 301 9908
Fax: 0203 301 9901
Contact: Niall Wharton

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