- Apply machine learning, deep learning, natural language processing, computer vision, and other AI techniques to various domains and use cases, to analyse large datasets and extract meaningful patterns and insights. Develop predictive models and algorithms to support business objectives.
- Explore and pre-process raw data to uncover trends, anomalies, and patterns.
- Create clear and compelling visualizations to communicate findings to both technical and non-technical stakeholders.
- Evaluate and optimize the performance, accuracy, and scalability of AI models and systems.
- Research and implement state-of-the-art AI methods and best practices.
- Collaborate with cross-functional teams of engineers, product managers, designers, and stakeholders, to understand business requirements and formulate data-driven solutions.
- Collaborate with domain experts to integrate domain knowledge into analytical models.
- Prototype, test, and productionise machine learning models. Monitor and optimize model performance over time.
- Model data for storage and querying in database and large-scale analytics platforms.
- Work with a wide variety of data types, from structured to unstructured, multimedia (video and still images), time-series and IoT data.
- Clearly visualise and communicate processes and results to clients, colleagues and other stakeholders.
- Support more junior colleagues and help develop the capabilities of the team.
- Work with colleagues across the firm to apply data science principles to specialist areas of the clients business.
- Hands-on experience with using, configuring and migrating ML models to Azure ML specifically a Kubeflow/Tensorflow stack (on prem), to a full managed Azure ML solution.
- A passion for developing and communicating deep and valuable insights.
- A highly rigorous mindset and approach to your work.
- In-depth knowledge of statistics and research methodology/experimental design.
- Extensive, demonstrable experience building and testing/validating machine learning models and using data mining techniques.
- Extensive experience of data modelling and database design.
- Demonstrable programming experience in Python and associated data science/ML libraries in Azure ML Tech Stack.
- The ability to form clear narratives that communicate complex ideas to diverse audiences.
- Experience of team leadership / supervising others.
- Experience of proposal writing, project costing, project management, etc.
- Ability to quickly make sense of new topics in unfamiliar fields.
- Specialist experience in a particular domain/application of data science, e.g. natural language processing, remote sensing, IoT.
- Experience of team leadership / supervising others.
- Ability to quickly make sense of new topics in unfamiliar fields.
- A Bachelor or Master degree in a computational field (Computer Science, Applied Mathematics, Engineering, or in a related quantitative discipline).
- Azure Certified Machine Learning Certification would be desirable.
At Version 1, we believe in providing our employees with a comprehensive benefits package that prioritises their well-being, professional growth, and financial stability.
One of our standout advantages is the ability to work with a hybrid schedule along with business travel, allowing our employees to strike a balance between work and life. We also offer a range of tech-related benefits, including an innovative Tech Scheme to help keep our team members up-to-date with the latest technology.
We prioritise the health and safety of our employees, providing private medical and life insurance coverage, as well as free eye tests and contributions towards glasses. Our team members can also stay ahead of the curve with incentivized certifications and accreditations, including AWS, Microsoft, Oracle, and Red Hat.
Our employee-designed Profit Share scheme divides a portion of our company's profits each quarter amongst employees. We are dedicated to helping our employees reach their full potential, offering Pathways Career Development Quarterly, a programme designed to support professional growth.
Laura Cowan
[email protected]
#LI-LC1
