Senior Data Scientist

Overview

Role:
Senior Data Scientist

Location:

Oxford, Harwell - Hybrid
Role :
Our vision is to create a safe and sustainable world. Ricardo, member of WSP, is a global strategic, environmental, and engineering consulting company. With over 100 years of engineering excellence and employing close to 3,000 employees in more than 20 countries, we provide exceptional levels of expertise in delivering leading-edge and innovative cross-sector sustainable products and solutions. Every day, we enable our customers to solve the most complex and dynamic challenges to help achieve a safe and sustainable world.

The Role

We are seeking a highly skilled Data Scientist with substantial Data Engineering capabilities to design, build, and deploy advanced analytical solutions. This hybrid role is ideal for a professional who is equally comfortable developing machine learning models, engineering robust data pipelines, and contributing to the broader technical architecture. The successful candidate will apply advanced analytical techniques, work with complex and large-scale datasets, collaborate with cross-functional teams, and support the development of high-quality data infrastructure enabling reliable, scalable data-driven decision-making.

Key Responsibilities

• Build, validate, and deploy sophisticated predictive and statistical models using modern Python-based libraries (e.g., scikit-learn, Tensor Flow, PyTorch).
• Conduct detailed exploratory data analysis, statistical modelling, hypothesis testing, and insight generation to support strategic business decisions.
• Develop high-quality, interpretable data visualisations using Matplotlib, Seaborn, and similar tools.
• Translate complex analytical outcomes into clear, actionable insights for both technical and non-technical stakeholders.
• Mentor junior team members and contribute to best-practice analytical approaches.

• Design and implement robust, scalable data orchestration pipelines using tools such as Airflow or Dagster.
• Work with big data technologies (Spark, Hadoop, Dask) to process and analyse large-scale datasets efficiently.
• Define and implement data models using ER diagrams, normalisation techniques (e.g., star schema, Snowflake), and modern ORM frameworks (e.g., SQL Alchemy).
• Provision, administer, and optimise relational databases, including schema design, indexing, and access management.
• Build high-performance APIs using frameworks such as FastAPI or Flask, following best RESTful design practices.

• Develop modular, maintainable, object-oriented Python code using advanced design patterns and testing practices (CI/CD, unit tests, code reviews).
• Containerise and deploy applications using Docker and Kubernetes; support infrastructure provisioning through Infrastructure-as-Code tools (e.g., Terraform, Ansible).
• Contribute to system architecture discussions, microservices design, and integration with cloud platforms (AWS, Azure).

• Work collaboratively across technical and non-technical teams to embed data-driven decision-making.
• Lead or support large-scale analytical or data engineering projects, ensuring adherence to best practices in code quality, reproducibility, and documentation.
• Provide mentorship, guidance, and support to colleagues, fostering a culture of learning and excellence.

• Python programming expertise, including functions, classes, modules, packages, and advanced OOP features.
• Strong statistical knowledge (degree-level or equivalent).
• Demonstrable experience in machine learning model development and evaluation.
• Proficiency with relational databases and database design.
• Experience designing and maintaining data pipelines and big-data processing workflows.
• Familiarity with containerisation, Kubernetes, CI/CD, and cloud infrastructure.
• Experience deploying models and data pipelines into production environments.
• Strong understanding of data modelling, APIs, and software engineering best practices.

• Strong problem-solving ability, capable of resolving ambiguous or complex…