Senior Data Scientist
From indie developers, games studios, to established publishers, GameAnalytics is currently the #1 analytics tool for anyone building a mobile game. Our network is approaching 100,000 games, which are played by more than 1 billion people each month.
What’s our mission? To help game developers make the right decisions based on data. And by joining our team, you’ll be working on new and innovative products to help tens of thousands of people in the industry do just that.
About the Data team
We're a highly collaborative and creative team of three Data Scientists and one Data Engineer focused on getting actionable insights from the vast quantity of data available to us. We are currently looking for a skilled Data Scientist to help us create models for new use cases, as well as improving accuracy of our current ones by trying new approaches and techniques, for topics such as churn, lifetime value estimation, customer segmentation, recommendation systems…
On the Data Team you’ll have the resources and data to learn what makes games go all the way from soft launch to industry hit, and the opportunity to help us engage our passionate community in a sector that’s seeing amazing growth. Your insights will help developers and studios understand their audience and improve their games by focusing on the most relevant topics to their players. As the largest games analytical firm globally, collecting ~100,000 events per second, resulting in 700Gb of (compressed) new data per day, you will not have time to get bored as a Data Scientist in GameAnalytics!
We are seeking an additional member to join the Data team family. You’ll need to be passionate about data and have a true drive for overcoming and solving technical challenges. The followed experience and / or skills are required:
- Deep understanding of AI and Machine Learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Random Forests, etc.
- Excellent applied statistics skills (probability distributions, regression, bayesian inference…)
- Ability to write high quality code in Python and experience with common data science toolkits, like Pandas, Numpy, Scikit-learn, SciPi, TensorFlow, Keras, etc.
- Experience using Big Data technologies: Hadoop, Spark, SQL/NoSQL databases…
- Experience working on end-to-end data science projects, from requirements gathering, to data discovery, modelling, validation, deployment and result communication.
- Exposure to cloud technologies. Bonus points for AWS and technologies such as EC2, EMR, Lambda, DynamoDB and S3.
- Experience working with complex data pipelines and ML in a production environment.
- Past experience within the private sector.
- Quick learner with an eagerness to work with new technologies.
- Ability to communicate with a wide range of people from different areas and to transfer knowledge to other team members.
- Food, snacks and drinks
- Entertainment Area
- Work Flexibility
- 25 Days paid holiday (excluding bank holiday)
- Company sickness leave
- Parental and guardian leave
- Additional compassionate leave
- “Work-from-Anywhere” Scheme
- Work equipment
- Learning budgets
- Monthly social nights
- Expense phone bill
- Cycle to work scheme