location_onBrighton, Truro TR2 4HD, UK
watch_later Posted: Jun 21, 2024
Skills Required
Nice To Have skills
Job Description
MPB customers come from all walks of life, and so do we. We are an Equal Opportunity Employer and do not discriminate against any employee or applicant because of family makeup, race, sexuality, religion, gender identity, disability or age. At MPB, every employee has the opportunity to make an impact and grow.
The Opportunity:
In this role, you will be working alongside the Senior Data Scientist to scale and elevate our current and future Data Science Data Products.
Key Responsibilities:
- Immerse yourself in our Pricing Optimization model approach. Help build improvements and understand, troubleshoot, and maintain the end-to-end process.
- Hands-on machine learning model development. Understand the nuances of the data gathering process and make modelling and data processing choices considerate of this.
- Own and contribute to our Data Science products. Suggest techniques, feature engineering, and deployment improvements. Collaborate effectively within a modern DS team using JIRA and version control best practices.
- Explore new Data Science opportunities. Conduct experiments, adapt approaches, and ensure scalability and deliverability
- Produce accessible and digestible outputs from ML products. This could be presenting findings in an accessible and concise way, designing Tableau dashboards to surface interactive predictions, delivering batch predictions or building API endpoints to serve online inference.
Who you are:
- Someone who already has a good theoretical background in Data Science techniques with a broad understanding of the most common approaches
- Ideally, you will have some commercial experience with an eagerness to learn and adapt in a fast-paced environment. You will apply critical thinking, design thinking, and pragmatism in this role.
- Someone who takes ownership of their projects and brings creativity, flexibility and enthusiasm to improving the deliverables
Required Skills:
- A solid understanding of the breadth of Data Science techniques and which are more appropriate for different types of business problems.
- Good competency in Python and SQL essential. Familiarity with different ways of working with Python and data desirable - e.g. virtual environment and dependency management, writing scripts and programs vs coding in Jupyter notebooks, working locally vs in cloud vm. Competency in transferable software engineering techniques like version control, CICD, software design patterns desirable.
- Familiarity with common ML packages, particularly scikit-learn and XGBoost or similar. Deep learning experience (e.g. Pytorch or Tensorflow) beneficial but not required
- Relentless appetite to learn and adapt techniques to business context. Prioritising adding value when shortlisting approaches. A focus on efficient data problem solving, be keen to deploy the most effective solution for the opportunity and have maturity in deciding where effort is spent
- Familiarity with GCP or alternatives like AWS highly desirable, bonus points for MLOPs elements such as vertex and cloud functions.
- Demonstrate a good understanding of the end to end deployment and management of Data Science products such as models. Ideally have experience owning or significantly contributing to production DS products but understanding the theoretical approach also valid with a desire to learn
- Great communication skills essential - be able to present outputs and updates of projects to varied audiences, adapt communication style and have influence over the stakeholders