Data Scientist

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 role

We 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.

• 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