Expoint - all jobs in one place

The point where experts and best companies meet

Limitless High-tech career opportunities - Expoint

Amazon Senior Data Scientist Ring Science Engineering 
Poland, Masovian Voivodeship, Warsaw 
420567559

20.11.2024
DESCRIPTION

Key job responsibilities
- Lead development and validation of state-of-the-art technical designs (causal inference, predictive tabular models, data insights/visualizations from EDA, etc)
- Drive shared understanding among business, engineering, and science teams of domain knowledge of processes, system structures, and business requirements.
- Contribute to the hiring and development of others
A day in the life
Translate/Interpret
• Complex and interrelated datasets describing customer behavior, messaging, content, product design and financial impact.Measure/Quantify/Expand
• Apply statistical or machine learning knowledge to specific business problems and data.
• Analyze historical data to identify trends and support decision making.
• Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
• Provide requirements to develop analytic capabilities, platforms, and pipelines.Explore/Enlighten
• Make decisions and recommendations.
• Build decision-making models and propose solution for the business problem you defined. Help productionalize them so they can be used systemically.
• Conduct written and verbal presentation to share insights and recommendations to audiences of varying levels of technical sophistication.
• Utilize code (Python/R/SQL) for data analyzing and modeling algorithms.


BASIC QUALIFICATIONS

- Bachelor's degree
- Industry experience as a Data Scientist
- Experience of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Experience with a wide variety of modelling approaches with an emphasis on causality (e.g. DML)
- Hands-on experience in modelling and analysis, and in deploying machine learning / deep learning models in production.