Data Scientist

The Data Analytics as a Service (da3s) team within Innovation & Engineering are looking for a data scientist to work on some of the important challenges bp is facing today. We operate as a consultancy within bp and work on a number of interesting problem spaces from the traditional oil and gas business through to renewables and our net-zero agenda, leveraging tools ranging from computer vision to timeseries forecasting.

Innovation & engineering

Join us in creating, growing, and delivering innovation at pace, enabling us to thrive while transitioning to a net zero world! All without compromising our operational risk management.

Working with us, you can do this by:

• Deploying our integrated capability and standards in service of our net zero and safety ambitions
• Driving our digital transformation and pioneering new business models
• Collaborating to deliver competitive customer-focused energy solutions.
• Originating, scaling and commercializing innovative ideas, and creating ground-breaking new businesses from them
• Protecting us by assuring management of our greatest physical and digital risks

Because together we are:

• Originators, builders, guardians and disruptors
• Engineers, technologists, scientists and entrepreneurs
• Empathetic, curious, creative and inclusive

Responsibilities

• 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 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.

Qualifications

• Hands-on experience designing, planning, prototyping, productionizing, maintaining and documenting reliable and scalable data science products in complex environments.
• Applied knowledge 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.
• Experience with big data technologies (e.g. Hadoop, Hive, and Spark) is a plus.
• Knowledge of experimental design and analysis is a plus.
• Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail.
• Strong stakeholder management and ability to lead large organizations through influence.
• Continuous learning and improvement mindset.
• MSc or PhD degree in a quantitative field.
• No prior experience in the energy industry required.

Legal Disclaimer :

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, sex, gender, gender expression, sexual orientation, age, marital status, socioeconomic background, neurodiversity/neurocognitive functioning, veteran status or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform crucial job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodations.

• deploying our integrated capability and standards in service of our net zero and ‎safety ambitions
• driving our digital transformation and pioneering new business models
• collaborating to deliver competitive customer-focused energy solutions
• originating, scaling and commercialising innovative ideas, and creating ground-breaking new ‎businesses from them
• protecting us by assuring management of our greatest physical and digital risks

• Originators, builders, guardians and disruptors
• Engineers, technologists, scientists and entrepreneurs‎
• Empathetic, curious, creative and inclusive