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Data Scientist – AdTech (ML & Reinforcement Learning), London, UK

Job Type:
Permanent
Job Sector:
Data, Technology
Job Category:
Data Science & Data Engineering
Country:
UK
Area:
London
Location:
London
Salary:
50,000 to 70,000 per annum
Salary Description:
benefits
Job Ref:
HQ00025340

Data Scientist – AdTech (ML & Reinforcement Learning)

Xcede's Data Science & Engineering team are working with a well-funded, high growth start-up who build real time solutions for the AdTech industry on a new Data Science role in their team. If you're interested in some of the most difficult problems (high load, low latency solutions) in the field and developing your skills with the latest big data technologies, this would be the ideal position for you. With an excellent existing Data Science team in place (including a founding team well regarded for their Machine Learning work in academic circles), they’re looking for another Data Scientist to come on board to handle the huge amount of work that they have on and help mentor junior Data Scientists.

Key Responsibilities:

- Lead Data Science projects and build ML algorithms at the core of the company’s product.
- Work alongside the commercial team members to understand relevant cases / requirements.
- Work alongside the Data Engineering team to productionise / deploy algorithms.
- Be an advocate for latest technologies & useful methodologies.
- Occasionally speak at events / raise awareness of the work being completed through academic publishing and patents.

Requirements:

- A relevant PhD / MSc in Computer Science, Maths, Stats or a related area.
- Excellent Python skills
- Previous commercial usage of Spark ideally
- Previous commercial experience working in an AWS environment (or similar)

Bonus Points!

- Previous work with Reinforcement learning and (/or) Deep Learning

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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