Consultant​/Senior Consultant- Advanced Analytics

Role Overview

As a Consultant/Senior Consultant, you are expected to manage onshore/client communication and mentor a team of analysts. This role focuses on advanced data analytics/sciences, designing and implementing analyses on patient‑level data or similar datasets.

• Communicate results to clients and team members
• Develop client relationships and serve as a key point of contact for the project
• Understand business objectives and develop models that help achieve them, along with metrics to track progress
• Analyze AI/ML algorithms to solve given problems and rank them by success probability
• Explore and visualise data to gain understanding and identify distribution differences that could affect performance when deploying the model in the real world
• Verify data quality and perform data cleaning
• Supervise data acquisition process if more data is needed
• Define validation strategies and data augmentation pipelines
• Specify preprocessing or feature engineering for a given dataset
• Train models and tune hyperparameters
• Analyse model errors and design strategies to overcome them
• Knowledge of deep learning techniques is an advantage
• Deploy models to production
• Interpret and analyse both qualitative and quantitative data points; build hypotheses with strong Excel and PowerPoint skills

• Foster a learning mindset in the team to proactively develop research and storytelling skills, leveraging multiple data sources to answer business questions
• Develop new capabilities leveraging new data sources and methods, including segment‑level analysis
• Engage with internal and external stakeholders to build effective relationships to create win‑win engagement models
• Mentor and guide team members who can benefit from your expertise and experience

• Bachelor’s or Master’s in Engineering
• 3–5 years of pharma/life science consulting experience
• High motivation, good work ethic, maturity, and personal initiative
• Strong oral and written communication skills
• Strong Excel and PowerPoint skills
• Adherence to client‑specific data privacy and compliance policies
• Knowledge of commonly used transactional data assets and others (e.g., volume/value, Rx, specialty‑level, longitudinal patient‑level data assets)

• Excellent interpersonal and communication skills (written and verbal)
• Innovative and collaborative behaviour, team player
• Customer centricity and attention to details