The Data Analytics team within the BP Supply & Trading, Trading Analytics organization comprises Quantitative Analytics, Data Strategists, Market Intelligence and Core Strategists. Linked by the common themes of data, numerical algorithms and technology, the team seeks to add value to the business by providing new models, tradable insights, distinctive data sets and agile technology solutions that empower the analyst community and advantage the commercial teams.
The Core Strategist team provides direct technology support to analysts, worldwide. Located in each of BP's main trading locations, these individuals possess expert IT knowledge and strong technical skills, combining deep programming know-how with practical experience of analytics, for example data science methods, statistics, numerical algorithms, derivative pricing or optimization. Tasked with providing prompt, practicable technology solutions to analysts day-to-day, they also partner with the central IT organization for strategic deliveries, including modern data repositories, data ontologies, new analytical toolkits, visualization technologies and cloud compute.
An opportunity for a Core Strategist is now available in our Chicago, London and New York office. Working in a close partnership with the head of oil analytics, you will design and build solutions to challenging business problems in a highly dynamic commercial environment.
- As part of a highly technical global team you will build direct relationships with key analysts and commercial stakeholders, understand their business requirements and immediate goals.
- Highly networked within both the 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 that enable analysts, inform decision making and drive revenue generation.
- 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. Provide input to IT and play a key interfacing role between them and the analyst community
- Act as a Trading Analytics Product Owner for strategic projects undertaken by the centralized IT teams in service of Trading Analytics.
Undergraduate degree in a quantitative discipline, (eg physics, mathematics, electrical engineering or mathematical finance), plus a postgraduate degree in a STEM subject. Strong academic record.
Essential experience and job requirements:
You will have deep practical experience and knowledge of:
- Python programming, including knowledge of pandas, numpy, Jupyter. Ability to write production ready, highly reliable, tuned (pythonic) numerical code.
- Web services architecture, ideally within Python context (flask, django). Practical experience building web applications and web services.
- Strong web technology skills and understanding, including HTML, CSS, XML.
- Knowledge of SQL and RDBMs.
- UI development, with a strong emphasis on data visualization. Knowledge of charting frameworks including Plotly, matplotlib and bokeh.
- Object oriented programming in a second language, for example Java, C++, C# or.NET.
- Software development industry best practice, including unit, integration and regression testing. Build and deploy patterns.
- Source code control systems, preferably Git.
Other essential skills and knowledge:
- Strong analytical, reasoning and mathematical skills.
- Strong written and verbal communication skills.
Desirable criteria and qualifications:
- Industry experience of large-scale data analysis and predictive modelling, preferably in a front office role in an investment bank, hedge fund or energy major.
- Quantitative skills, for example knowledge of statistics, probability theory, optimization or derivative pricing.
- The scientific python stack including SciPy, scikit-learn, Statsmodels and possibly Keras, Theano, Tensorflow and NLTK.
- Data science knowledge. To include econometrics, OLS and Lasso, Logistic Regression, CART and Random Forests, SVMs, NNs, Radial Basis Functions and Kernel methods. Regularization and validation.