Expoint - all jobs in one place

מציאת משרת הייטק בחברות הטובות ביותר מעולם לא הייתה קלה יותר

Limitless High-tech career opportunities - Expoint

Amazon Data Scientist OpsTech Infra Eng 
United States, Texas, Dallas 
989233009

09.09.2024
DESCRIPTION

As a Data Scientist, you will be responsible for data exploration and analyses, as well as AI model development. You will collaborate with data engineers to collect, preprocess, and maintain high-quality datasets. You will dive deep into the available data, identifying trends, patterns, and insights to inform AI initiatives. You will design, develop, and implement AI models, including machine learning and deep learning algorithms, to solve complex business challenges, ensuring that these models are optimized for accuracy, scalability, and real-time performance. You will support the deployment of AI models into production environments, ensuring efficient and reliable operation, and own the model performance monitoring, make improvements, and implement retraining strategies. Strong business and communication skills are essential for collaborating with business owners to develop key business questions and build solutions that provide answers and drive change.Key job responsibilities
Thinking Big and generating ideas with the stakeholders.Scoping long-term solutions as a series of smaller, more manageable iterations.
Creating data science architectures, and building scalable solutions along with the data engineers.
Running simulations, measuring performance, building ML models and designing optimization algorithms.
Supporting existing models, while thinking about next generation solutions.
Keep up-to-date with the latest AI research, technologies, and industry best practices.


BASIC QUALIFICATIONS

- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment