Data Scientist

Data Scientist

Organisation McKesson

Location: London, UK

Application Deadline: 30 days remaining

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 productionise 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 optimise 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 junior analysts, guiding best practices in advanced analytics and modelling while 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 visualisation tools.
• Stay abreast of industry trends in pharmaceutical supply chain analytics, regulatory changes, and data science methodologies.

(The above statements describe the general nature and level of work being performed in this job. They are not intended to be an exhaustive list of all duties.)

Required 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

Bachelor’s degree (Master’s or PhD preferable) in Mathematics or a heavily quantitative field.

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