Job Overview
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 470+ across 9 offices, all growing and learning together since our launch during the pandemic. Here, you won't be stuck in a cubicle. Instead, you'll be out in the open water, shaping the future with brilliant minds. Ready to join our epic growth journey?
What are we looking for?
As a Senior Data Scientist, you will play a key role in delivering end-to-end data science solutions across pharmaceutical and healthcare engagements. The role demands a blend of technical depth, business acumen, and scientific curiosity. You will translate complex business problems into analytical frameworks, develop scalable machine learning and statistical solutions, and generate actionable insights that drive commercial, clinical, and operational impact for clients and patients worldwide. Beyond technical execution, you are expected to think strategically, framing business challenges, designing analytical approaches, and guiding clients toward the most effective data-driven decisions.
Key Responsibilities
- Own day-to-day execution of data science projects from problem definition to deployment, ensuring methodological rigor, business relevance, and timely delivery while supporting the development and mentorship of the juniors.
- Build, tune, and validate advanced machine learning and statistical models, including supervised techniques (classification, regression, uplift), unsupervised methods (clustering, PCA, GMM), deep learning, transformer models, and analytical frameworks (hypothesis testing, causal inference, survival analysis) using industry-standard libraries
- Develop clean, modular, and production-ready code with reusable components, adhering to best practices in version control, documentation, and scalable pipeline design for deployment in production or client-facing environment
- Synthesize insights from diverse data sources, including claims, prescription (LAAD), lab, EMR, and unstructured text, into clear narratives driving client decisions tailored to patient, HCP, and market contexts
- Partner with seniors and cross teams to develop analytical solutions, delivering clear and actionable insights to client
- Support client engagements through solution design and storyboarding, while contributing reusable ML assets, accelerators, and documentation to enhance team capabilities
Must have
- 3.5 - 5.5 years of hands on experience in Data Science and ML
- Strong hands-on experience in Python, PySpark, and SQL for manipulating and handling large structured and unstructured datasets
- Strong foundation in machine learning algorithms, feature engineering, model tuning, and evaluation techniques
- Proficiency in data visualization (Power BI, Tableau, MS Office suite or equivalent) and in translating analytical results effectively.
- Ability to structure ambiguous business problems, design analytical roadmaps, and communicate insights effectively to both technical and non-technical stakeholders
- Exposure to MLOps frameworks, including MLflow, Docker, Airflow, or CI/CD pipelines, to automate model training, deployment, and monitoring in scalable production environments.
- Qualification: Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or related fields