As a market leader in fuel pricing and network planning technologies, Kalibrate develops and delivers strategy and technology solutions to drive greater value from the fuel and convenience retail chain.
In a highly dynamic and fast-paced environment, this position will provide the successful candidate with a unique opportunity to develop and apply state-of-the-art machine learning and artificial intelligence techniques and methods to interpret, analyse and model data, to address specific business problems. You will play a vital role in introducing new computational and decision analysis techniques to support strategically important future business development.
- Develop and apply knowledge of mathematical and statistical analysis to improve dynamic pricing and network planning software, to provide competitive pricing and presence in the marketplace.
- Design, execute, analyze and interpret pricing experiments to understand real time dynamics of a highly competitive retail market.
- Develop, document and analyze metrics, analytics, and insight generators for pricing strategy and network planning optimization.
- Identify a potential business problem, or take a business problem originated by others, and create a solution that allows repeatable analysis, and productization of the solution.
- Report analysis and results to senior management.
- Actively participate in project meetings by offering feedback on assigned tasks and gather additional information from internal members linked to the analysis project.
- Increase skills on a continuous basis to remain current with new processes, methodologies and techniques.
- Communicate with international regional office personnel during non-business hours as required.
- Collaborate with development team to create a single integrated library of intellectual property with appropriate management processes, and work with them in implementing models in a production data-streaming environment integrating Apache Kafka with Alteryx, R and Keras.
- A Master’s degree in Statistics, Mathematics, Operations Research, Economics, Computer Science or a related engineering/science degree is preferred. A PhD in a related field is a plus.
- One to three years of mathematical and/or statistical analysis work experience is required, preferably in the commercial arena.
- Experience in the following areas:
- 1. Expertise in statistical and mathematical methods, including: mathematical modeling and regression; supervised and unsupervised machine learning for data analytics, prediction and classification.
- 2. Knowledge of advanced statistical concepts, including: time-series analysis, Bayesian models and optimization.
- 3. High proficiency in programming with a scientific software language – preferably R, or Python
- 4. Demonstrate an ability to create innovative solutions to complex problems, suggest new and enhanced modeling methodologies to meet future business requirements., and to review others’ designs.
- 5. Motivated to lead oneself, with a desire and ability to learn new mathematical/statistical skills and techniques.
- 6. Demonstrate a strong desire to work in a team environment, share knowledge and facilitate the sharing of knowledge between peers and to communicate with others within the department and company in both written and oral format.
- 7. Ability and desire to understand the business domain and engage with non-technical staff and clients, and to present material in a fashion appropriate to the audience
- Experience in the following areas is advantageous:
- 1. Knowledge of econometrics (e.g., elasticities, pricing, market competition models).
- 2. Deep learning with Keras or Tensorflow
- 3. Familiarity with programming in SQL and using Microsoft SQL Server Management Studio
Applications should be directed to Phillip Hartley at Aspire Data Recruitment –firstname.lastname@example.org
/ +44 (0)1706 825 199