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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.
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