2 of 2 Data Scientist Jobs in Oxford

Our Transformatics team builds data and AI products to provide analytics insights to clients and teams involved in transformation programs across the globe. The current team is composed of data engineers, data scientists and product managers who are spread across several geographies. The team covers a variety of industries, functions, analytics methodologies and platforms – e.g. Cloud data engineering, advanced statistics, machine learning, predictive analytics, MLOps and generative AI. What You’ll Do You will collaborate closely with a team comprising data scientists, data engineers, product developers, and analytics-focused consultants. You will work on topics such as descriptive analytics, predictive models (e.g., boosted trees), and large language models (LLMs), particularly for segmentation use cases. … so, you will help bring advanced analytics capabilities into one of flagship products, named "Wave". Your work will be the backbone for how client runs future Transformations, leveraging data science assets, to improve the odds of success for our clients. In this role, you will be involved in the following areas: ● Advanced insight generation: transforming complex business questions More ❯

The TVC Analyst will play a crucial role in transforming complex data sets into actionable insights, contributing to projects that have a social impact. The role involves addressing stakeholder requests and developing a robust data analysis infrastructure. Key responsibilities: • Impact Analysis: Design and execute in-depth analyses to measure the impact of various projects in to-be-determined … efforts. • Insight Communication: Translate complex data findings into clear, visually compelling reports and dashboards customised for a diverse set of collaborators. • Ad Hoc Analysis: Provide prompt and accurate responses to data-driven queries from various collaborators. • Collaboration: Work closely with teams to identify data needs and support project objectives through impactful insights. • Data Infrastructure Development: Develop … and maintain data pipelines for clean, organised, and accessible data. Role requirements: • Programming Proficiency: Mastery in data analysis tools such as SQL and Python. • Statistical Expertise: Understanding of statistical techniques like hypothesis testing, regression modelling, and experimental design. • Data Storytelling: Translate technical findings into understandable narratives and visuals for a non-technical audience. • Problem-Solving: Analytical mindset More ❯