Senior Data Scientist - Operation Research
Role details
Job location
Tech stack
Job description
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Responsible for refactoring the Optimization algorithm written in Python using Object Oriented Programming
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Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG.
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Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to Pricing Optimization.
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Develop and implement predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource allocation across the supply chain.
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Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
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Design and execute experiments to evaluate the effectiveness of different replenishment strategies and allocation policies.
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Monitor and analyze key performance indicators (KPIs) related to replenishment and supply chain allocation, and provide recommendations for continuous improvement.
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Stay abreast of industry trends and best practices in data science, replenishment optimization, and supply chain management, and leverage this knowledge to drive innovation within the organization.
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Collaborate, coach, and learn with a growing team of experienced Data Scientists.
Requirements
We are looking for a Senior Data Scientist with a good blend of data analytics background, practical experience in Operation research strategies and Pricing Analytics within supply chains, and strong coding capabilities to add to our team., * Proven experience 6+ years working as a Data Scientist, with a focus on supply chain optimization and inventory allocation.
- MS or PhD in Computer Science, Operations Research, Applied Mathematics, Machine Learning, or a related field.
- Experience with using mathematical programming solvers such as Gurobi, Xpress MP, CPLEX, or Google OR Tools in applications.
- Experience with MLflow and model lifecycle management
- Experience building end-to-end ML pipelines in production
- Solid understanding of statistical methods, optimization techniques, and predictive modelling concepts.
- Strong proficiency in programming languages such as Python, Pyspark and SQL, and experience working with data analysis and machine learning libraries.
- Ability to apply various analytical models to business use cases
- Exceptional communication and collaboration skills to understand business partner needs and deliver solutions and explain to business stakeholders.
Benefits & conditions
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.