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Job Description
Structured overview of role & requirementsAbout This Role
Lead end-to-end development and scaling of advanced forecasting models using statistical, ML, and AI methods for commercial demand and planning.
Translate ambiguous business challenges into scalable analytical workflows and partner with stakeholders across Finance, Commercial, Market Access, and Analytics to influence strategic decision-making.
Design, deploy, and maintain enterprise forecasting platforms and ensure best practices in MLOps, while mentoring junior team members and adopting emerging AI/ML technologies.
Minimum Requirements
2–5 years of experience in applied machine learning and data science problem-solving roles.
Bachelor’s, Master’s, or Ph.D. in Data Science, Computer Science, Statistics, Engineering, or related field.
Proven expertise in time-series forecasting techniques (ARIMA, Prophet, Holt-Winters) and Python-based data science workflows.
Experience with large structured and unstructured datasets (SQL, NoSQL) and MLOps tools (MLflow, Git, CI/CD, containerization).
Ideal Candidate Profile
Operates with high autonomy in ambiguous, fast-paced environments, independently managing forecasting workstreams.
Combines deep statistical and ML expertise with stakeholder leadership and strong communication skills to drive business impact.
Experienced in integrating advanced AI/ML and autonomous agent technologies into commercial forecasting and analytics workflows.