Sr. Data Scientist

MSL McKesson Strategic Services Limited
London
2 days ago
Create job alert

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 itsinceptionin 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. This partnership leverages McKesson’sdemonstratedstrength andexpertisein global pharmaceutical sourcing in conjunction with Walmart’s strength and commitment to delivering leading health and wellness services to their customers.

The environment in which ClarusONE operates constantly requires the organisation to adapt and change, seeking greater efficiency in how it works through improved process, technologyinnovationand new ways of working. Delivering these changes with discipline and rigour will ensure that they land with maximum impact, delivering for ourMembersand 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 Title:Data Scientist

Location:[London, United Kingdom]

Level:P4

Reportsto:Senior Manager,Insights & Data Science

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. AtClarusONE, we play a pivotal role in enabling efficient supply chain models and delivering value to ourMembersthrough innovative sourcing and data-driven solutions.

TheData Scientistwill be instrumental in advancingClarusONE’sanalytics 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 toanticipatesupply disruptions, pricing shifts, and demand fluctuations.

Collaborate withEngineering andProduct teams to productionize data science solutions withinClarusONE’stechnology 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 andoptimizedecision-making.

Build andmaintainanalytical 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 toidentifyhigh-impact opportunities foradvancedanalyticsapplications.

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.

ChampionClarusONE’sdata 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.

(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/Basic Qualifications

5 years’ experience indata science, advanced analytics, or statistical modelling roles.  General ML modelling experience - Azure ML Proficiencyin Python or R for statistical analysis, machine learning, and data manipulation. Experienceinstatistical 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 ofMLOpspractices 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 riskmodellingin 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 autonomouslyand comfortable with ambiguity. Experience in the healthcare field, preferably in generic pharmaceuticals (pricing,sourcingor distribution) preferred, though notrequired.

Education/Experience 

Bachelorsdegree (Mastersor PhD preferable) in Mathematics or a heavily quantitative field.

McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind:

McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.


McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.

McKesson job postings are posted on our career site: .

Related Jobs

View all jobs

Senior Data Scientist — Live Product Analytics

Senior Data Scientist, Live Product Analytics

Senior Data Scientist, Live Product Analytics

Data Scientist

Senior Data Scientist

Senior Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.