Job Summary:
The forecasting and planning Research (FPR) team in SPS estimates potential future risk on the Amazon platform and its stores using state-of-the-art machine learning algorithms and translates those estimates into the investigator headcount requirement in each country.
Responsibilities:
- The data scientists will be responsible for modeling complex problems, discovering insights, and identifying opportunities using statistical, machine learning, algorithmic, data mining, and visualization techniques.
- They are also responsible for moving the models to the production environment and automating with appropriate drift monitoring and model improvement processes.
- They will need to collaborate effectively with internal stakeholders and cross-functional teams to understand requirements, solve problems, create operational efficiencies, and deliver successfully against high organizational standards.
- The candidates should be able to apply a breadth of tools, data sources, and analytical techniques to answer a wide range of high-impact business questions and present the insights concisely and effectively.
- The candidates should be effective communicators capable of independently driving issues to resolution, communicating insights to non-technical audiences, and documenting the artifacts. This is a high-impact role with goals that directly impact the bottom line of the business.
Key Deliverables/Outcomes:
- Development of accurate and reliable workforce forecasting models.
- Automate training and forecasting by deploying data and model pipelines on AWS cloud infrastructure with drift monitoring with emphasis on accuracy and speed
- Building Project launch impact estimates model using tools such as analytics, time series, probability, and deep learning.
- Reduce MAPE (forecasting accuracy) across different risk functions.
- Automate data ingestion for Project inputs from Excel to forecasting models
- Improved data quality through rigorous cleaning and transformation processes and automating them.
- Clear documentation of the code and artifacts.
- Actionable insights derived from data analysis to support strategic decisions.
- Experiment with the latest forecasting algorithms & processes to optimize existing modeling infrastructure.
Qualifications Needed:
- 5+ years of data scientist experience, preferably with Forecasting systems & Operational Research
- 3+ years of data querying languages (e.g. SQL) and scripting languages (e.g. Python) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- 3+ years of AWS cloud experience building end-to-end products deploying, monitoring, and updating them using tools such as Amazon SageMaker pipelines and docker containers.
- Experience applying theoretical models in an applied environment
- Understanding of demand forecasting & impact on operational capacity planning
- Knowledge of time series models and deep learning for time series are an asset.
Send your resume to: India-careers@vertisystem.com