Data Scientist in London

ClarusONE Sourcing Services, LLP, provides strategic generic pharmaceutical services for both Walmart Stores, Inc. and McKesson Corporation. Its mission is to enable access to affordable medicines, which it has successfully been doing since its inception in 2016. ClarusONE is a joint venture between Walmart and McKesson, two of the top 10 biggest corporations in the USA, according to the Fortune 500 list. They have more than two decades of history working together to improve the quality and lower the cost of pharmaceutical care to patients.

The environment in which ClarusONE operates constantly requires the organisation to adapt and change, seeking greater efficiency in how it works through improved process, technology innovation and new ways of working. Delivering these changes with discipline and rigour will ensure that they land with maximum impact, delivering for our Members and for the patients that they serve. ClarusONE Sourcing Services is headquartered in London and prides itself on its can-do attitude that has ensured millions of Americans pay less when buying generic pharmaceuticals every day.

Job Purpose

The highly competitive US generic pharmaceutical sector continues to challenge every element of the supply chain. In this dynamic environment, patients are served through evolving channels, while manufacturers, distributors, and dispensers must adapt to shifting market forces, payer dynamics, and regulatory frameworks. At ClarusONE, we play a pivotal role in enabling efficient supply chain models and delivering value to our Members through innovative sourcing and data-driven solutions. The Data Scientist will be instrumental in advancing ClarusOne’s analytics capabilities by applying statistical modelling, machine learning, and predictive analytics to complex business problems. This role will drive the development of scalable data science solutions that inform strategic sourcing, risk mitigation, and operational efficiency. The Data Scientist will collaborate cross-functionally to embed advanced analytics into technology platforms and decision-making processes, supporting the long-term vision and goals of the business.

Responsibilities

• Develop and deploy statistical models, machine learning algorithms, and forecasting tools to support strategic sourcing, supplier risk assessment, and market dynamics.
• Lead exploratory data analysis and hypothesis-driven investigations to uncover actionable insights and inform business strategy.
• Design and implement predictive models to anticipate supply disruptions, pricing shifts, and demand fluctuations.
• Collaborate with Engineering and Product teams to productionize data science solutions within ClarusONE’s technology platforms.
• Apply rigorous statistical techniques to evaluate sourcing strategies, supplier segmentation, and product lifecycle dynamics.
• Champion experimentation frameworks (e.g., A/B testing) to assess impact of sourcing initiatives and optimize decision-making.
• Build and maintain analytical pipelines using Python, R, SQL, and cloud-based platforms.
• Communicate complex analytical findings clearly to stakeholders across technical and non-technical audiences.
• Partner with business functions to identify high-impact opportunities for advanced analytics applications.
• Act as a subject matter expert and mentor to junior analysts, guiding best practices in advanced analytics and modelling while clearly communicating technical insights to diverse audiences.
• Champion ClarusONE’s data assets and lead the adoption of innovative, data-driven approaches across the full analytics lifecycle—from prototyping to resolving complex data issues.
• Contribute to the development of strategic insight products that integrate data science with business intelligence and visualization tools.
• Stay abreast of industry trends in pharmaceutical supply chain analytics, regulatory changes, and data science methodologies.

Required/Basic Qualifications

• 5 years’ experience in data science, advanced analytics, or statistical modelling roles.
• Proficiency in Python or R for statistical analysis, machine learning, and data manipulation.
• Experience in statistical modelling techniques such as regression, time series forecasting, clustering, classification, and survival analysis.
• Experience delivering POCs, shaping early-stage analytics functions, and building new workflows.

Preferred Qualifications

• Knowledge of MLOps practices and deployment of models into production environments is a plus.
• Experience designing and executing A/B tests, causal inference studies, and experimental frameworks.
• Strong understanding of supply chain dynamics, sourcing strategy, and risk modelling in a regulated environment.
• Time management, including ability to organise and prioritise work to consistently meet critical and/or conflicting daily deadlines while ensuring the highest level of accuracy.
• Ability to build positive working relationships with internal and external business partners and to influence a diverse set of stakeholders.
• Strong SQL skills and experience working with large-scale relational and cloud-based databases (e.g., Snowflake, BigQuery).
• Experience with machine learning frameworks (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch).
• Ability to work autonomously and comfortable with ambiguity.
• Experience in the healthcare field, preferably in generic pharmaceuticals (pricing, sourcing or distribution) preferred, though not required.

Education/Experience

• Bachelors degree (Masters or PhD preferable) in Mathematics or a heavily quantitative field.