Data Scientist

Requirements

Your Technical Skill Set:

• Research expertise in a specific domain.
• They are looking for depth here. Show us you have spent infinite hours breaking apart something 90% of people likely think is irrelevant.
• A PhD is a good start, but spending years working on data for a specific company is just as good.
• Expertise in video games.
• Not necessarily in terms of skill proficiency since they have plenty of people with that expertise, but you need to game seriously and understand the vernacular.
• Self sufficient with analysis tools.
• You need to be able use your toolset to interact and work closely with engineers in a development environment.
• Their current team works with: Python, Spark, Kafka, Airflow.
• Additional experience with SQL, NOSQL databases as well as Anaconda libraries is a plus.
• Here are some things that are a huge plus.
• Golang experience.
• Aerospike experience.
• Deploying models in Google Cloud.
• Expertise with machine learning.
• Deep understanding of linear models, decision trees, and neural networks with the goal of finding new ways to apply that knowledge to generate meaningful insights.
• Bonus points if this has been the day to day of your thesis for the last few years.

Your Personal Skill Set:

• Plays games with a desire to improve.
• They’d love it if you are someone who plays the games they create their tools around currently, but are open to people who love games and the tools that players use to get better at them.
• No, they don’t care if you are Bronze or Diamond.
• Self-initiated, fast learner with a positive attitude.
• Hopefully, you’ll tell us what they need to be doing. Independence and agency are key traits at Mobalytics.
• They want to queue with “Can do” party members because passion breeds enthusiasm, which in turn makes learning and team achievement infectious.
• Strong sense of team spirit thriving in a fast-paced environment.
• They strive for excellence and don’t waste each other's time with BS.
• They all support and encourage each other, and that also means being good at listening to feedback.
• Excellent attention to details, quality of work and time management.
• You have ownership of the product. Be proud of your work, not for their sake, but for yours. They will be proud too.
• Working hard and having a sense of urgency are important, but being efficient is more important. Hard work doesn’t mean endless hours and “face-time,” it means on time delivery of quality work and achieving their shared goals.
• English is a must.

What they are expecting from you

• Deliver data science and data engineering projects from idea to completion.
• Develop the idea, create a plan, layout the methodology, collaborate with other departments, execute the plan, and provide recommendations based on results. Here are some examples.
• Process games played on a specific patch and identify and bucketise patch related information for different purposes.
• Enhance their GPI(Gamer Performance Index) algorithm.
• Create recommendations based on players historical data.
• Thoroughly document data science processes and code, and develop strategies to ensure they are safe, secure, and reproducible.
• Visualize data to communicate results and findings to the product teams.
• Help us to optimize legacy code and refactor existing data processing pipelines.

Company offers

• Remote & flexible.
• Company retreats.
• Equity stake in the company.
• Mandatory gameplay time.
• Personal growth budget.

Useful links

• Article about Mobalytics on Rusbase: link.
• Article about Mobalytics on VC.ru: link.
• Article about Mobalytics on ITC.ua: link.
• Article about Mobalytics on Forbs: link.