Associate Data Scientist

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