Back
Strong employer brand, mid-level generalist title, metro location, and broad skill requirements increase candidate competition.
Advanced ML and OR skills transfer across industries, though consumer goods domain knowledge moderately matters.
Explicit 2–4 years requirement plus mandatory ML, cloud, and framework skills increases filtering rigor.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and productionize scalable data science algorithms using machine learning, optimization, simulation, and advanced AI techniques.
Collaborate closely with Data and AI Engineering teams to deploy models and handle large datasets in cloud environments.
Mentor and coach others technically, becoming an expert in specific data science methodologies and demonstrably improving business outcomes.
Bachelor's, Master's, or postgraduate degree in quantitative field such as Operations Research, Computer Science, Engineering, Applied Mathematics, Statistics, or related.
2-4 years of relevant work experience in data science or related domain.
Proficiency in Python and familiarity with machine learning libraries like OpenCV, scikit-learn, PyTorch, TensorFlow/Keras, and Pandas.
Experience developing and testing code in cloud environments; strong communication skills with ability to influence.
Experienced in applying advanced analytic methodologies (Machine Learning, Optimization, Simulation, Generative and Agentic AI) to real-world business problems.
Comfortable working in collaborative environments partnering with domain experts and engineering teams to translate models into production solutions.
Ready to take ownership of brand-related projects with measurable impact and continuously develop deep technical expertise while mentoring peers.