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- Full-time
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Description
About ProcDNA
ProcDNA is a global consulting firm. We fuse design thinking with cutting-edge tech to
create game-changing Commercial Analytics and Technology solutions for our clients.
We're a passionate team of 400+ across 8 offices, all growing and learning together
since our launch during the pandemic. Here, you won't be stuck in a cubicle - you'll be
out in the open water, shaping the future with brilliant minds. At ProcDNA, innovation
isn't just encouraged, it's ingrained in our DNA.
What you’ll do
• Collect, clean, and process large datasets from multiple sources
• Develop and test advanced machine learning algorithms and models to solve problems in a computationally efficient and statistically effective manner
• Analyze and interpret data to identify trends, patterns, and insights by executing statistical and data mining techniques
• Visualize data and present findings to stakeholders
• Document code, models, and experiments to ensure reproducibility and maintainability
• Collaborate with cross-functional teams to identify business problems and develop data-driven solutions
• Communicate project progress and results to relevant stakeholders
• Stay up to date with the latest data science techniques and tools
Must have
• Bachelor's/Master’s program in Data Science, Computer Science, Statistics, Mathematics, or a related field
• Good understanding of the US pharmaceutical landscape and its key stakeholders.
• Hands-on experience or exposure to segmentation, predictive analytics, forecasting, and causal inference modeling use cases.
• Proficient in Python and must know about libraries like (Pandas, Scikit-Learn, Matplotlib, TensorFlow, etc.); SQL, R is a plus
• Good understanding of data manipulation, statistical analysis, and machine learning concepts
• Ability to work independently and manage multiple tasks simultaneously
• Strong attention to detail, with a research-focused mindset
• Excellent critical thinking and problem-solving skills
• Excellent communication - should be able to describe findings to a technical and non-technical audience
• Familiarity with data visualization tools such as Tableau, Power BI or R Shiny is a plus
• High motivation and good work ethic is a must
ProcDNA is a global consulting firm. We fuse design thinking with cutting-edge tech to
create game-changing Commercial Analytics and Technology solutions for our clients.
We're a passionate team of 400+ across 8 offices, all growing and learning together
since our launch during the pandemic. Here, you won't be stuck in a cubicle - you'll be
out in the open water, shaping the future with brilliant minds. At ProcDNA, innovation
isn't just encouraged, it's ingrained in our DNA.
What you’ll do
• Collect, clean, and process large datasets from multiple sources
• Develop and test advanced machine learning algorithms and models to solve problems in a computationally efficient and statistically effective manner
• Analyze and interpret data to identify trends, patterns, and insights by executing statistical and data mining techniques
• Visualize data and present findings to stakeholders
• Document code, models, and experiments to ensure reproducibility and maintainability
• Collaborate with cross-functional teams to identify business problems and develop data-driven solutions
• Communicate project progress and results to relevant stakeholders
• Stay up to date with the latest data science techniques and tools
Must have
• Bachelor's/Master’s program in Data Science, Computer Science, Statistics, Mathematics, or a related field
• Good understanding of the US pharmaceutical landscape and its key stakeholders.
• Hands-on experience or exposure to segmentation, predictive analytics, forecasting, and causal inference modeling use cases.
• Proficient in Python and must know about libraries like (Pandas, Scikit-Learn, Matplotlib, TensorFlow, etc.); SQL, R is a plus
• Good understanding of data manipulation, statistical analysis, and machine learning concepts
• Ability to work independently and manage multiple tasks simultaneously
• Strong attention to detail, with a research-focused mindset
• Excellent critical thinking and problem-solving skills
• Excellent communication - should be able to describe findings to a technical and non-technical audience
• Familiarity with data visualization tools such as Tableau, Power BI or R Shiny is a plus
• High motivation and good work ethic is a must
Skills
PythonSQLMachine LearningTensorFlowPandasScikit-learnData ScienceTableauPower BI
