Tiger Analytics is looking to solve complex business problems for Fortune 500 companies by generating valuable insights from their data using advanced analytics, Data Science, Machine Learning, and AI.
Requirements
- 7+ years of hands-on experience in Python and PySpark.
- Data Science: Strong expertise in developing supervised and unsupervised ML models, with knowledge of time series and demand forecasting being a plus.
- Experience working with semiconductor resourse.
- Strong expertise in mathematical optimization models (mixed-integer linear programming).
- Experience in Machine Learning
- Experience in Data Science
- Industry- Supply chain is must have
Responsibilities
- Accelerate and improve the entire network design process, from raw data to a model ready for running in tools like Coupa or Llamasoft.
- Getting data and identifying/correcting outliers in capacity, throughputs, and transportation costs.
- Creating models for auto-completion of missing data and new routes.
- Automating the creation of common scenarios, such as optimizing warehouse locations (deleting or adding warehouses) in a dynamic and globally applicable way.
- Connecting multiple isolated models- The core of this involves mathematical optimization models (mixed-integer linear programming).
- Combine data science with supply chain knowledge to adapt to available data.
- Develop heuristics to accelerate NP-hard network design models that currently take days to run.
Other
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
- 7+ years of experience in Data Science and Machine Learning.
- Strong stakeholder management skills, including engagement with business units and vendors.
- Collaborate with cross-functional teams
- Drive business value through advanced analytics
