Position: Data Scientist
Company: Neurons Lab
Category: Data Science
Experience required: 5y
English level: fluent

**Objective**

Deliver successful projects in the iGaming industry

**Areas of Responsibility**

⦿Statistical modeling and hypothesis testing
⦿Designing, training, and validating results from a breadth of machine learning algorithms
⦿Writing clean, efficient SQL
⦿Building and testing Python applications
⦿Building deep neural networks with modern tools, such as PyTorch or ⦿Tensorflow
⦿Collaborating via Git

**Skills**

⦿Machine learning and engineering
⦿Statistical modeling
⦿Data mining and analysis
⦿Advanced English, good communication with business stakeholders
⦿Documentation development

**Experience**

⦿Experience with online learning, reinforcement learning, contextual bandits algorithms
⦿Experience in launching and validating online campaigns using A/B testing or the above-mentioned methods
⦿Prior experience in online gaming, e-commerce, and entertainment or similar industries

**Allocation: 20-30 h/ week**

**We Offer**

⦿Scientific or engineering challenges
⦿Work with disruptive deep-tech startups
⦿Work with rock stars (senior-level engineers, Ph.D.)
⦿Meaningful social and environmental projects
⦿Transparent, professional growth plan depending on your impact
⦿Remote work from any location
⦿Flexible working hours
⦿ Unpaid unlimited personal time off
⦿ Regular Team Building & company-wide team events

For those applying for this position:

Questions:

1. Do you have a strong background in ML, and enjoy applying theory to develop real-world applications, with expertise in personalized machine learning algorithms?

2. Do you apply techniques such as classification, clustering, regression, Deep Learning (CNN, RNN, GANs), and Reinforcement learning methods to build scalable solutions?

Please share examples of the things you have built, such as products developed online or projects contributed to on GitHub.

3. Do you have hands-on experience implementing production machine learning systems at scale in Python?

4. Do you have experience with large-scale, distributed data processing frameworks/tools and cloud platforms like AWS?