Description

GameAnalytics is one of the world's most popular mobile analytics tools used in a huge network of games that are played by more than 1.5 billion people each month (equating to over of the world's mobile gamers). We have an exciting opportunity for a machine learning expert to take a leading role in the development of a promising new product line.

We're looking for a skilled Data Scientist to help us create prediction models for the games industry, as well as improve the accuracy and scale of our data by implementing new ML, AI and NLP approaches and techniques. You'll work collaboratively with our expanding data, engineering, and product teams to ensure that we deliver market-leading insights and benchmarks, building upon our unique first-party dataset. You'll have a good memory and be able to visually understand complex data structures.

Key responsibilities

Working on end-to-end data science projects, from requirements gathering to data discovery, modelling, validation, deployment, and result communication
Building predictive models and machine-learning algorithms using many different modelling algorithms or using different training data sets
Present information using data visualization techniques
Analyze large amounts of information to discover trends and patterns
Undertake collection, preprocessing and analysis of structured and unstructured data
Identify valuable data sources, and work with engineering teams to automate collection processes
Proposing solutions and strategies to business challenges that surface unique insights about the games industry
Collaborate with engineering and product development teams to build better customer experiences and a richer breadth of insights

Requirements

Proven experience as a Data Scientist or Data Analyst, ideally at a SaaS company
You understand the workflow and life cycle of machine learning and are familiar with platforms for end-to-end production ML pipelines (e.g. TFX, MLFlow, Sagemaker)
Knowledge of SQL and Python (in particular - common data science toolkits like Pandas, Numpy, Scikit-learn, SciPy, TensorFlow, Keras); familiarity with R, PHP, Scala, Java or C++ is an asset
Experience in data mining and working with complex data pipelines and ML in a production environment (you can apply DevOps principles to big data projects)
Experience using NoSQL databases; familiarity with Couchbase preferred
Deep understanding of AI and Machine Learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Random Forests, etc.
Ability to communicate with a wide range of people from different areas and to effectively transfer knowledge to other team members
Problem-solving aptitude and strong math skills (e.g. statistics, algebra)
An analytical mind and business acumen relating to the games industry

Desirable

Exposure to cloud technologies. Bonus points for AWS and technologies such as EC2, EMR, Lambda, DynamoDB and S3
Excellent applied statistics skills (probability distributions, regression, Bayesian inference...)
Experience with multilingual natural language processing, particularly text analysis, semantic analysis, automated keyword extraction etc. Experience using NLP libraries like NLTK and spaCy is a bonus
Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
Experience within the private sector, gaming specifically being very desirable

Benefits

Remote working flexibility - or part-time remote
(When in office) Food, snacks and drink
Entertainment Area
25 days paid holiday (excluding bank holiday)
Company sickness leave
Parental and guardian leave
Additional compassionate leave
"Work-from-Anywhere" Scheme
Learning budgets
Monthly social nights
Expense phone bill
Cycle to work scheme

Please note that you will be hired under a PEO arrangement for remote roles located outside of the UK and Denmark. This is to ensure that our benefits are not in violation of local employment laws.

Summary
Company name: GameAnalytics
Remote job title: Data Scientist - GameIntel - Remote (Europe) at GameAnalytics () (allows remote)
Job tags: machine learning, rlang, algorithm

Data Scientist GameIntel