Senior Data Scientist

Project Leadership and Collaboration (Primary Focus):

• 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

Advanced Analytics (Primary Focus): 

• 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

Marketing and Experimental Analytics (Primary Focus):

• 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

GenAI, NLP, and Machine Learning Operations (Secondary / Emerging Focus): 

• 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

• Enhance agent performance through experimentation with LLMs, prompt tuning, and advanced reasoning workflows

Communication, Mentorship, and Governance (Primary Focus):

• 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

• Promote best practices in coding, data handling, and project management within the data science team, ensuring high-quality deliverables

• Ensure adherence to Roche’s ethical AI standards and data privacy regulations

Who you are:

• 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 fi