LYTT

Data Scientist

Sept. 12, 2022

Anywhere

LYTT is a growing technology venture backed by bp. Leveraging machine learning and cloud based computing, we have designed and deployed ground-breaking technology that turns data captured from sensors deep under the Earth’s surface into actionable information. We listen for sounds (such as liquids or solids entering a space) and generate insights from the data – our solution has been described as the Shazam of sensor data - giving our customers a thorough understanding of exactly what is happening across their assets in real time. Our technology has already generated hundreds of millions of dollars of value for our customers. We have a brilliant team of people and we’re building a culture that celebrates innovation. With over 16 nationalities, a breadth and depth of expertise with a mix of interests, we are proud to bring diverse thinking to the energy industry’s most challenging problems.About the roleWe are looking for a Data Scientist to join our brilliant team where you will have a unique opportunity to work on A LOT of Distributed Fibre Optic Sensing (DFOS) data acquired both in a lab and in the field, develop machine learning based models for real-time applications, deploy algorithms in production and solve some of our customers biggest challenges.For more information on what it’s like to be a Data Scientist at LYTT, check out our blog: https://medium.com/lytt-publications/a-month-at-the-speed-of-lytt-c9aec0847e22. Role Responsibilities Use LYTTs suit of algorithms to analyze data from oil wells and other sources, work together with a domain expert to validate the results and present the findings to the customer. Develop machine learning algorithms to provide actionable insights from real-time data taken from fiber optic sensors, helping to improve safety in the oil and gas sector and reduce the global carbon footprint. Contribute to building a team that cultivates collaboration and innovation. Requirements Demonstrable experience in solving real world regression and classification problems. In-depth knowledge of different modelling techniques for both supervised and unsupervised problems. Proficiency with Python and analytical tools like numpy, pandas, scikit-learn, jupyter, matplotlib and seaborn. A track record of data-driven modelling and of deploying machine learning models into production ready systems. Nice to have (but not required) Experience with delivering B2B projects. Knowledge of Signal Processing. Familiarity with modern machine learning techniques such as domain adaptation and transfer learning. Benefits Flexible working We're happy for you to be fully remote within the UK 25 days annual leave A (genuine) commitment to wellness Enhanced parental leave Annual bonus Equity Private Medical Insurance A brilliant team, who care

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