Senior Data Scientist - Replenishment Optimization

Toronto, Ontario, Canada - Remote

Tiger Analytics

An Advanced Analytics and AI consulting services company. Trusted Data sciences, Data engineering partner for Fortune 1000 firms.Simplify data. Explore more

View company page

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 Senior Data Scientist with a good blend of data analytics background, who holds practical experience in optimizing replenishment strategies and allocating resources within supply chains and has strong coding capabilities to add to our team.

Key Responsibilities:

  • Responsible for refactoring the Distribution 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 CPG.
  • Utilize advanced statistical techniques and data science algorithms to analyze large datasets and derive actionable insights related to replenishment optimization and supply chain allocation.
  • 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.

Requirements

  • Proven experience 6+ years working as a Data Scientist, with a focus on replenishment optimization and supply chain allocation.
  • Bachelor's or Master's degree in Computer Science, Statistics, Operations Research, or a related field.
  • Solid understanding of statistical methods, optimization techniques, and predictive modelling concepts.
  • Strong proficiency in programming languages such as Python, 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.

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.

Apply now Apply later
  • Share this job via
  • or

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Computer Science Consulting Data analysis Data Analytics KPIs Machine Learning Python Research SQL Statistics

Perks/benefits: Career development

Regions: Remote/Anywhere North America
Country: Canada
Job stats:  6  0  0
Category: Data Science Jobs

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.