Tiger Analytics is seeking an experienced Senior Data Scientist to join their team.
The company is a leading advanced analytics consulting firm that assists Fortune 500 companies in generating valuable insights from their data.
The role involves working on cutting-edge projects and collaborating with cross-functional teams to drive business value through advanced analytics.
Key responsibilities include accelerating and improving the network design process, from raw data to a model ready for tools like Coupa or Llamasoft.
The position requires getting data and identifying/correcting outliers in capacity, throughputs, and transportation costs.
The candidate will create models for auto-completion of missing data and new routes.
Automating the creation of common scenarios, such as optimizing warehouse locations in a dynamic and globally applicable way, is also a key responsibility.
The role involves connecting multiple isolated models, primarily using mathematical optimization models (mixed-integer linear programming).
The candidate will combine data science with supply chain knowledge to adapt to available data.
Developing heuristics to accelerate NP-hard network design models that currently take days to run is essential.
The goal is to automate the running of hundreds of models in the background to provide possible improvements without manual intervention.
Supply chain analysis responsibilities include normalizing historical data to accurately reflect the supply chain and removing anomalies.
The candidate will identify when and why the real supply chain deviates from the plan and analyze bottlenecks in the supply chain.
Finding general insights that analysts might not know to look for, such as unexpected correlations between events across different parts of the supply chain, is required.
The candidate will identify trends where operations are outside of normal parameters for any KPI or action in the supply chain.
Requirements:
A Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field is required.
The candidate must have 7+ years of experience in Data Science and Machine Learning.
A minimum of 7+ years of hands-on experience in Python and PySpark is necessary.
Strong stakeholder management skills, including engagement with business units and vendors, are essential.
The candidate should have strong expertise in developing supervised and unsupervised ML models, with knowledge of time series and demand forecasting being a plus.
Experience in the supply chain industry is a must-have.
Hands-on experience with Python, PySpark, and SQL for data querying and statistical modeling is required.
Benefits:
The position offers the opportunity to work on innovative solutions to complex business problems.
Employees will have the chance to collaborate with cross-functional teams and contribute to cutting-edge projects.
The role provides a platform to drive business value through advanced analytics.
Working at Tiger Analytics allows for professional growth in a leading advanced analytics consulting firm.
