Senior Data Scientist - Operation Research
Listed on 2026-07-20
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IT/Tech
Data Scientist, Machine Learning/ ML Engineer, Data Analyst, AI Engineer (Applied/Software)
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.
Responsibilities- Responsible for refactoring the Optimization algorithm written in Python using Object Oriented Programming
- Work on the latest applications of data science to solve business problems in the Supply chain and optimization space of Retail and/or CPG.
- Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to Pricing Optimization.
- Develop and implement predictive models and optimization algorithms to improve inventory management, reduce stockouts, and optimize resource allocation across the supply chain.
- Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
- Design and execute experiments to evaluate the effectiveness of different replenishment strategies and allocation policies.
- Monitor and analyze key performance indicators (KPIs) related to replenishment and supply chain allocation, and provide recommendations for continuous improvement.
- 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.
- Collaborate, coach, and learn with a growing team of experienced Data Scientists.
- 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.
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.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
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