Please note that we work in hybrid model, 3 days in the office and 2 days remotely.
We are searching for a passionate Data Scientist to help with our Machine Learning tasks and statistical analysis.
Main Duties & Responsibilities:
- Work with business and technical stakeholders to choose the most appropriate Machine Learning solutions;
- Design and develop ML models for use-cases like:
- recommender systems
- fraud detection
- chat text analysis
- Work with data engineers to select appropriate datasets and data representation methods;
- Work with game developers to make sure that the necessary data are available;
- Research and implement appropriate ML algorithms and tools;
- Devise metrics and evaluation processes for the performance and impact of your models;
- Train, test and retrain ML models;
- Work with other team members to deploy ML models to production;
- Use and, where necessary, extend existing ML libraries and frameworks.
Requirements
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University degree in numerical field (Machine Learning, Statistics, Mathematics, Computer Science, Physics, Engineering, etc.);
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Proven track record and excellent ability to understand, interpret and explain business data;
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At least 3 years of work experience in the Data Science field;
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Experience and understanding of linear algebra and statistical modelling;
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Experience with deploying ML solutions to production;
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In-depth knowledge in at least one ML field such as regression, classification, clustering, pattern mining or optimization;
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Experience with at least one ML framework such as Scikit-Learn, Keras, Tensorflow, Pytorch, MLLib;
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Hands-on with Python, in particular packages such as Pandas, Numpy, Matplotlib (or equivalent);
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Experience with SQL and Big data tools such as Spark/Hive;
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Highly proficient in spoken and written English;
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Excellent communication skills and a pragmatic approach to problem solving;
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Willingness to learn and interest in latest trends in programming and ML.
Nice to Have:
- Knowledge of Scala or Java;
- Experience with AWS or other cloud provider;
- Experience with Kafka, Clickhouse, Postgres, Kubernetes, Docker.
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