Data Scientist

Data Scientist (Pharma)

Fully remote (UK/Ireland/Europe)

Salary up to £75k depending on experience

MBN Solutions are delighted to have been retained by their client, a powerhouse in the Pharmaceuticals industry, to onboard a talented and innovative Data Scientist to join the team. This Data Scientist will help rocket the business into the future, masterfully crafting, launching, and fine-tuning cutting-edge Advanced Analytics Models. You will be the person behind transforming raw data into actionable insights, ensuring the organisation makes decisions that are not just informed but inspired. 

The Job:

Data Modelling:End to end model development & refining, with best practice in mindAnalysis delivery:Deliver Advanced analytics to support Commercial decision makingSystem evolutions:Evolve Advanced analytics toolkit with new functionalities to better support the businessData Management: Ensure all data required for the advanced analytics are available, clean, consistent and documentedData cleansing:Eliminating noise and errors in data while ensuring consistency across areasData delivery: Ensure all data required for the advanced analytics is available, clean, consistent, easily accessible and documentedAnomaly detection & management:Identification of analysis areas of interest and investigation into theseSupport to business:Support the business with needed insights coming out of Advanced AnalyticsTeam education:Educate the organisation on data, data science, Analytics, AI and data to improve data literacy across the businessData visualisation:Creation of optimised business views in Power BI to enable the business to make decisions using our data science modelsData stack enrichment:Feed the data stack with new data sources and ensure this supports better decision makingAdvanced analysis improvements :Implement new analytical methods to improve business understanding through new ways to use dataData Science Roadmap:Ideate and help define our data strategy with new insights using new models, frameworks and capabilities that can be single-market or business wideContinuous Model Engineering:Ensure that model creation is not the end of the process – continual improvement & calibration is to be implemented

Skills and experience this Data Scientist needs to have:

Strong experience with regression, classification and clustering in complex data (sparsity, missingness, fast-changing, etc.) and business environments (LoE, competitive analysis, research horizon scanning, etc.) platforms (frameworks, techniques and libraries, expertise working with large data sets, end-to-end model building with a view to scale from the beginning) Expertise in writing models (and code) that is readable, documented, well tested and robust in production for scaling. Easy identification of model drift and rectification Expansive knowledge of the business & industry data ecosystem. Can determine and correct data quality issues as well as identification of additional data sources for inclusion in the pipeline Experienced in data management, governance, data & modelling lifecycles (ML Ops). Seek to improve model efficiency, performance, and scalability

Microsoft Technology Stack experience sought (Azure Data Lake, Databricks, Azure ML, Power BI), and capabilities of programming in and understanding R & Python.

You will also likely have:

A passion for problem-solving and innovation: tackling key data problems experimenting with cutting edge DS, ML & AI techniques, frameworks and models. Eager & willing to learn new techniques, approaches and data science tools Not afraid to push boundaries, failing fast, establishing best practice with all development and has a keen interest in ethical & responsible model development (including knowledge of Data legislation e.g. GDPR) Advanced capability in data story-telling, bringing people on a journey using insights discovered in the data Good business acumen, teamwork, approachable & good business ethic as standard Project management skills, project estimation, ppt creation & presentation capabilities Entrepreneurial mindset, driven, organised & not phased by remote/virtual work