Senior Data Scientist

Job Description You will work with Being part of the P&O Digital Delivery data group, you will apply your experience and familiarity with domain data processes to support the P&O organization across teams such as Wells & Subsurface, Production and bp Solutions. These teams provides daily operational data management, data engineering and analytics support to this organization across a broad range of disciplines, applications and business requirements.

Let me tell you about the role:

A data scientist applies scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Their key responsibilities include gathering and analyzing large sets of data, using machine learning algorithms, statistical models, and data processing techniques to predict future trends and provide actionable insights. A machine learning engineer designs and develops artificial intelligence (AI) systems that can learn and make decisions autonomously. Their key responsibilities include creating and optimizing machine learning models, developing algorithms that enable machines to perform tasks without explicit programming, and working with large datasets to train these models. They collaborate with data scientists, software engineers, and domain experts to implement machine learning solutions that address specific business needs. Additionally, machine learning engineers are responsible for ensuring the scalability and efficiency of machine learning systems, continuously improving model performance through thorough testing and validation, and staying updated with the latest advancements in the field to integrate innovative techniques into their work.

What you will deliver Part of a cross-disciplinary team, working closely with other data scientists, data engineers software engineers, data managers and business partners. Build scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers.

Carry out data analyses to yield actionable business insights. Adhere to and advocate for data science best practices (e.g. technical design, technical design review, unit testing, monitoring & alerting, checking in code, code review, documentation). Present results to peers and senior management. Actively contribute to improve developer velocity. Mentor others.

What you will need to be successful (experience and qualifications):

Essential MSc or PhD degree in a quantitative field. Hands-on experience designing, planning, prototyping, productionizing, maintaining and documenting reliable and scalable data science products in complex environments. Applied knowledge as part of a team (if not leading) of data science tools and approaches across all data lifecycle stages. Thorough understanding of underlying mathematical foundations of statistics and machine learning.

Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++) Basic SQL knowledge. Customer-centric and pragmatic approach.

 

Travel Requirement

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