Data Analyst (Pharmaceutical Industry)

Job Description

The healthcare firm I'm working with specializes in data analytics and consulting services, aiding pharmaceutical and diagnostic companies to enhance patient testing and treatment pathways through data-driven solutions. Their goal is to improve patient outcomes by streamlining the diagnostic testing process for patients with complex diseases. Currently, they're searching for a talented Associate Data Analyst Director to join their team, bringing their data visualization capabilities to the next level.

As an Associate Data Analyst Director, you will need a strong analytical mindset and experience performing advanced analytics to provide insights supporting pharmaceutical commercialization.

Requirements:

  • Experience in healthcare data analytics, including segmentation and targeting, for pharmaceutical companies is desirable
  • Knowledge of relational database querying with SQL and data wrangling using tools such as KNIME to manage large amounts of complex data
  • Proficient skills in Microsoft Office Suite
  • Proven knowledge and skills using data preparation tools such as KNIME, SQL-based database queries, programming languages for analysis such as R, Python, XML, Javascript, and reporting software like Tableau/Power BI
  • Working understanding of pharmacy, EHR, claims, and lab data and how commercial pharmaceutical functions can use these data sets.
  • Demonstrated curiosity for data exploration and improvement of business questions using new analytical methods
  • Excellent interpersonal and communication skills for successful collaboration with internal and external stakeholders and customers
  • Self-starter ability, with evidence of having worked independently and on your initiative.

Responsibilities:

  • Collaborate with project teams to deliver projects
  • Develop data strategies based on client requirements
  • Utilize KNIME and SQL language to manipulate data for the database.
  • Manage large volumes of complex healthcare data from various sources effectively
  • Interpret complex project requirements and rules from stakeholders and convert them into technical specifications, including parameters, custom groups, calculations, aggregations, filtering criteria, and more.
  • Utilize SQL-based database queries and programming languages such as R, Python, XML, and Javascript for analysis.
  • Apply critical thinking and problem-solving methodologies to identify process improvements and ensure top-notch operational performance.

The company offers a range of benefits, including a competitive salary, for the successful candidate. If you're interested in this role or any other position in Data Engineering, Data Science, or Data Warehousing, please contact Rachel Boyle directly on LinkedIn.