Data Scientist
Rate - £500 - £700/day Outside IR35 *TBC
Location – Fully remote
Length - 3-month contract
Position Overview
The Data Scientist will play a critical role in advancing the organisation's data analytics and machine learning capabilities, driving predictive insights and optimisation across various business units. This role is integral to designing and implementing advanced analytical solutions, supporting units such as Trading, Customer & Travel Product Development, Hospitality, and Digital Marketing. Collaborating with peers and stakeholders, the Data Scientist will navigate the complexities of a dynamic business environment shaped by migrations, acquisitions, and evolving competencies.
Core Responsibilities
- Collaboration:
Work closely with Trading, Finance, Marketing, and Customer teams to understand data needs and provide actionable insights. Collaborate with data engineering, governance, and the wider technology team to optimise workflows and ensure cohesive solutions. - Project Contribution:
Drive data science projects from inception to completion, prioritising tasks based on business impact. Ensure timely delivery of high-quality analytical solutions in collaboration with senior leads. - Data Analysis & Modelling:
Perform advanced data analysis to identify trends, patterns, and insights. Develop, validate, and deploy predictive models to optimise business processes, continuously refining existing algorithms. - Reporting & Communication:
Develop dashboards and reports to monitor KPIs and communicate findings to stakeholders. Present complex data insights in clear, actionable formats to support process and technology improvements. - Data Strategy:
Contribute to shaping the organisation's data strategy, identifying opportunities for leveraging data to drive innovation. Lead the development of predictive models, algorithms, and analytical tools aligned with strategic goals. - Decision-Making Responsibilities:
The Data Scientist will be instrumental in problem-solving and implementing improvements in data science processes and technologies. Making informed decisions on data modelling, solution design, and stakeholder engagement. Ensuring solutions adhere to industry best practices for reliability, efficiency, and scalability.
Knowledge, Experience, and Skills
- Technical Expertise:
Proficient in Python and SQL for data access, analysis, and interpretation. Experience collaborating with Data Engineering to optimise workflows and infrastructure. Experience working with Databricks or similar unified analytics platforms to streamline data engineering pipelines, optimise workflows, and facilitate collaborative data science projects. - Machine Learning & Statistical Analysis:
Strong background in statistical analysis and machine learning techniques. Familiarity with advanced models, such as Gradient Boosting Machines (GBMs), Neural Networks, and Large Language Models (LLMs). - Tools & Platforms:
Hands-on experience with ML Flow, Amazon Sagemaker, TensorFlow, PyTorch, or similar platforms. Ability to deploy robust and scalable machine learning solutions in production environments. - Agile Methodologies:
Experience working in Agile or Kanban frameworks using tools like Jira and Confluence. Proven ability to manage projects in iterative delivery cycles. - Communication & Stakeholder Engagement:
Strong communication skills to distil complex methodologies into actionable insights for diverse audiences. - AI Implementation (Bonus):
Interest or experience in implementing AI solutions to enhance processes and drive innovation. - Other Skills:
Meticulous attention to detail with a focus on quality deliverables. Ability to work both independently and as part of a collaborative team.
Why Join?
This is a unique opportunity to shape and contribute to an innovative data-driven culture within a growing organisation. With cutting-edge projects and a diverse set of challenges, the Data Scientist will have a significant impact across multiple domains, driving both immediate results and long-term strategic initiatives.
To apply, please email (url removed)