Responsible for providing relevant models and analytical insight that directly influence, support & surface commercial activities using advanced technical and analytical expertise, identifying process improvements and working with stakeholders and analytics colleagues to share information and ideas, build models, and develop tools and systems.
The core strategists provide direct technology support to analysts, worldwide to help build models and analytical insight that directly influences commercial outcomes. We are Python experts located in each of our main trading locations and combine deep programming know-how with practical experience of analytics - data science methods, statistics, numerical algorithms, regression analysis or commercial skills. We provide timely, technology solutions to analysts within oil and products, gas and power and low carbon and partner with the central IT organisation for strategic deliveries, including modern data repositories, data ontologies, new analytical toolkits, visualisation technologies and cloud compute
Essential experience and skills
- You will build direct relationships with key analysts to understand their business requirements and immediate goals.
- Highly networked within both the global Core Strategist team and the central IT organization you will play a leading role in advancing the analyst technology agenda across regions.
- Be held by the business as a deep technical authority and source of expert guidance to the analyst community. Provide day-to-day problem solving support and proactively share best practice.
- Create efficient, resilient and innovative solutions using modern data analytics technologies
- Partner with analysts to develop custom interactive dashboard visualization solutions using web technologies and third-party frameworks.
- Design and build scalable, reusable components and frameworks in-line with mandated architectures. Rigorously adhere to software development best practice for enterprise-grade applications.
- Make significant contributions to the shared proprietary model libraries for use by analysts globally.
- Work with the architecture and infrastructure teams in central IT to ensure that designs are aligned with the company technology strategy. Play a key interfacing role between IT and the analyst community
Desirable experience and skills
- Undergraduate degree in STEM subject or quantitative discipline.
- Deep practical experience and knowledge of Python programming for numerical data analysis, including strong knowledge of pandas, numpy, Jupyter. Solid hands-on knowledge of time series data manipulation. Ability to write production ready, highly reliable, tuned (pythonic) numerical code.
- Deep understanding of web services, ability to integrate with REST APIs.
- Good knowledge of SQL and RDBMs and strong experience in cloud technology concepts and stack, specifically AWS services.
- You create engaging visual reports with a strong emphasis on data visualization. Knowledge of visualisation frameworks including Plotly, Plotly Dash and PowerBI.
- You adhere to software development industry best practice, including unit, integration and regression testing. Build and deploy patterns. Source code control systems, preferably Git.
- Strong analytical, reasoning and mathematical skills.
Considering Joining bp?At bp, we support our people to learn and grow in a diverse and exciting environment. We believe that our team is strengthened by diversity. bp is committed to encouraging an inclusive environment in which everyone is respected and treated fairly. There are many aspects of our employees’ lives that are meaningful, so we offer benefits to enable your work to fit with your life. These benefits can include flexible working options, a generous paid parental leave policy, excellent retirement benefits, and excellent Benefits.
- Understanding of web technologies including HTML, CSS, XML.
- Understanding of time series forecasting, quantitative skills, e.g. statistics, probability theory, OLS and Lasso, Logistic Regression
- Experience of working with data science platforms - especially DataIKU
- Experience with the following data sources, pricing models and related tools: ONS, CCEE, BBCE, NEWAVE, DECOMP, PROSPEC/NORUS.
- Object oriented programming in a second language, for example Java, C++ or C#
- The scientific python stack including SciPy, scikit-learn, Statsmodels and possibly Tensorflow or NLTK.