Senior Data Scientist – Operation Research

🕒 May 25

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Tiger Analytics

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

🤖 Artificial Intelligence

🤝 B2B

Artificial Intelligence • B2B • Consulting

Tiger Analytics is a leading AI and analytics consulting firm that specializes in leveraging data science and machine learning to provide strategic business insights across various industries. They offer services in data strategy, AI engineering, and business intelligence to enable data-driven decision-making and digital transformation for their clients. Tiger Analytics collaborates with top technology partners like Microsoft, Google Cloud, and AWS to deliver cutting-edge solutions. They serve a diverse range of sectors including consumer packaged goods, healthcare, and finance, helping businesses operationalize insights and differentiate with AI and machine learning technologies.

📋 Description

• Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce. • We are also market leaders in AI and analytics consulting in the CPG & retail industry with over 40% of our revenues coming from the sector. This is our fastest-growing sector, and we are beefing up our talent in the space. • 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. • **Key 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 Pricing techniques. • - Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions. • - 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.

🎯 Requirements

• - Proven experience 10+ 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. • - 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

• 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.***