Senior Data Scientist

Role Overview

• Lead and manage end-to-end data science projects from problem definition to model deployment ensuring alignment with business goals and timelines
• Partner with cross-functional teams to define business requirements and deliver tailored analytics solutions
• Develop and maintain key stakeholder relationships to ensure effective communication and collaboration throughout project lifecycles
• Present analytical findings and strategic recommendations to business stakeholders, influencing data-driven decision making across multiple levels of the organization
• Collect, clean, and prepare large and complex healthcare-related datasets (product performance, patient data, operational metrics, etc.) for analysis
• Develop and implement statistical and machine learning models (e.g., multivariate regression, time-series analysis, XGBoost, clustering, classification, causal inference) to address complex business problems and uncover meaningful insights
• Utilize advanced data analytics techniques to explore and identify patterns, trends, and root causes, applying methodologies such as clustering, classification, and causal inference
• Build Econometric/market mix models (MMM), multi-touch attribution models (MTA), optimize marketing spend and come-up with implementable recommendations and strategy/plan
• Lead the development and implementation of advanced Media Mix Models to inform and optimize marketing spend across multiple channels (e.g., TV, digital, print, radio)
• Design and execute complex statistical analyses to evaluate the effectiveness of marketing strategies and optimize resource allocation
• Apply experimental design and A/B testing methodologies to validate and measure marketing and operational initiatives
• Develop and implement GenAI models and tools to solve business problems
• Deploy machine learning models in production environments, ensuring robust ML Ops practices for model monitoring, maintenance, and scaling
• Collaborate with IT and DevOps teams to streamline the integration of ML models into existing systems and workflows
• Translate complex data insights into clear and actionable business strategies that address stakeholder needs and expectations
• Mentor and guide junior data scientists, providing technical expertise and fostering an environment of continuous learning and improvement

Requirements

• You hold a bachelor's degree in Technology or a relevant discipline, with a preference for Computer Science, Software, Statistics, Data Science, AI, Machine Learning, Data Engineering and related fields.
• Preferably, you have a Master's degree
• Certifications in AI/ML, Data Science, or related technologies would be a plus
• You have 5-8 years of hands-on experience in data science, with proven experience in leading data science projects within the pharma/biotech/healthcare domain
• Strong proficiency in Python and SQL, with experience in data wrangling, feature engineering, and analytical model development
• Experience working in cloud-based environments (AWS preferred), with practical knowledge of GitHub and cloud computing workflows for data science projects
• Hands-on experience building models using algorithms and techniques such as multivariate regression, time series analysis, XGBoost, clustering, classification, OLS regression, Naïve Bayes, linear and time-decay attribution models, Markov chains, and Shapley value methods
• Experience in Multi channel Marketing Mix Modeling (MMM), or related fields, with a track record of delivering impactful results
• At least 4 years of strong experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, Keras, spaCy, NLTK, NumPy, pandas, and Spark
• Basic understanding of pharmaceutical datasets (e.g., IQVIA, SHA, Patients data) and familiarity with US healthcare markets would be a plus
• Strong analytical and problem-solving skills with a data-driven mindset.

Tech Stack

• AWS
• Cloud
• Keras
• Numpy
• Pandas
• Python
• PyTorch
• Scikit-Learn
• Spark
• SQL
• Tensorflow

Benefits

• health insurance
• retirement plans
• paid time off
• flexible work arrangements
• professional development