Data Science Lead, ANSA McAL Limited

The Data Science Lead will be required to use innovative modeling and simulation methodologies to analyze Real World Evidence (RWE) and contribute to critical decision-making.

Job Summary:

• The Data Science Lead will be required to use innovative modeling and simulation methodologies to analyze Real World Evidence (RWE) and contribute to critical decision-making. They will be responsible for providing Functional Management with demand forecast and supply analysis to enable effective operational planning & decision-making, drive system and process innovation within team and the larger organization to address stakeholder needs in alignment with organizational strategy and vision. They will also provide direction, coaching and mentorship for staff to deliver quality forecasting outputs, and execute special projects and assignments.

Job Description:

• Work with cross functional teams and other analytics professionals to identify business opportunities and frame the analytics problem.
• Obtain, manipulate, clean, and analyze structured and unstructured data from diverse sources.
• Build & validate advanced analytical and statistical models, using forecasting, optimization, simulation, and machine learning techniques (e.g., NLP, computer vision, tabular modeling)
• Deploy models as proofs of concept or fully productionized implementations.
• Monitor and maintain deployed models to ensure continued effectiveness.
• Quantify business impacts and communicate actionable recommendations with business partners to drive informed decisions.
• Promote data driven decision making across the company by delivering workshops and tutorials.

Education and Experience Requirements:

• Master’s/PhD degree in a quantitative discipline (e.g., Operations Research, Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, etc.)
• 2+ years’ experience with at least one programming language (e.g., Python, R, C++, Java)
• Depth of knowledge in at least one OR/ML skill area (e.g., Optimization, Simulation, Machine Learning, Statistics)
• Experience with SQL and Data Visualization.
• Practical experience with Data Extraction, cleaning, and analysis.
• Experience in using cloud platforms and parallel processing to scale model development/ deployment.
• Excellent verbal and written communication skills.
• Strong time management and organizational abilities.