Position: Data Scientist
Company: Eleks
Category: Data Science
Experience required: 2y
English level: upper

**Responsibilities**
- Collecting, transforming, and preprocessing raw data to prepare it for analysis
- Deriving descriptive statistics out of the preprocessed data
- Building statistical and probabilistic models
- Designing, developing, training, and testing data mining, machine learning, and artificial intelligence models and algorithms
- Providing comparative research on different algorithms and models

**Requirements**
- Practice in general data science (machine learning, deep learning, exploratory data analysis, NLP, CV, time series analysis)
- Knowledge and hands-on experience with one or more of the following Python frameworks usage (SciPy, NumPy, PyTorch, Scikit-learn, TensorFlow, etc.)
- Skills in simple deployment (API, docker)
- Understanding theoretical concepts of statistics/probability, data mining, machine learning
- At least an Upper-Intermediate English level is a must
- Ability to work independently with limited supervision
- Ability to handle multi-tasking activities
- Master's degree in Mathematics, Physics, Computer Science or similar

**What will you get with ELEKS**
- Above average compensation and competitive Social package
- Close cooperation with a customer
- Challenging tasks
- Competence development
- Ability to influence project technologies
- Projects from scratch
- Team of professionals
- Dynamic environment with a low level of bureaucracy
- Medical insurance

**ABOUT ELEKS** 
Eleks is a custom software development company. We deliver value to our clients, thanks to our expertise and experience gained from working as a software innovation partner since 1991.

Our 2000+ professionals located in the Delivery Centers across Eastern Europe and sales offices in Europe and North America, provide our clients with a full range of software engineering services. These include product development, QA, R&D, design, technology consulting, and dedicated teams.