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Data Scientist

2 months ago

Glasgow, Glasgow City, United Kingdom MBN Solutions Full time

MBN Solutions is partnering with a leading force in the pharmaceutical industry to find a talented and innovative Data Scientist. This role will play a crucial part in shaping the future of the company by developing, implementing, and refining cutting-edge advanced analytics models.

As a Data Scientist, you'll be responsible for transforming raw data into actionable insights that drive informed decision-making within the organization. You'll work closely with stakeholders to understand their needs and deliver impactful analytical solutions.

Your Responsibilities:
  • Develop and refine advanced analytics models from end to end, adhering to best practices.
  • Deliver insightful analyses to support strategic commercial decision-making.
  • Continuously evolve the advanced analytics toolkit by incorporating new functionalities that enhance business capabilities.
  • Ensure data integrity by managing, cleaning, and documenting all data required for advanced analytics.
  • Identify and investigate areas of interest within the data through anomaly detection and analysis.
  • Provide valuable insights to the business based on your analytical findings.
  • Educate the organization on data science concepts, fostering a culture of data literacy.
  • Create compelling visualizations in Power BI to enable data-driven decision-making.
  • Enrich the data stack by integrating new data sources and ensuring they support effective decision-making.
  • Implement innovative analytical methods to deepen business understanding through data exploration.
  • Contribute to the development of a comprehensive data science roadmap, incorporating new models, frameworks, and capabilities.
  • Continuously improve and calibrate existing models to ensure optimal performance and scalability.
Your Skills and Experience:
  • Proven experience in developing regression, classification, and clustering models within complex data environments (e.g., handling sparsity, missingness, and fast-changing data).
  • Expertise in writing robust, well-documented, and production-ready code for model development and deployment.
  • Deep understanding of the pharmaceutical industry's data ecosystem, including data quality management and identification of potential new data sources.
  • Experience with data management, governance, and the ML Ops lifecycle. A focus on model efficiency, performance, and scalability is essential.

Familiarity with Microsoft technologies such as Azure Data Lake, Databricks, Azure ML, and Power BI is highly desirable. Proficiency in R and Python programming languages is also expected.