About the job
The Data Science team is looking for an ML Engineer that will be responsible for providing solutions for betting user experience. Some key projects include customer profiling, recommendation systems, automating pricing based on liability, exploring winning betting strategies etc. The role will be based in Athens.
Key Responsibilities:
- Fetch appropriate data from the data-lake.
- Apply data cleansing methods to identify corrupt or inaccurate data entries.
- Apply Machine Learning techniques to identify patterns in the data.
- Create modelling pipelines in Python based on betting data that automates the model parameters upon demand.
- Evaluate and maintain existing models.
- Document the process followed.
- Report to the Data Science Manager on workflow and share findings with the Data Science team.
- Collaborate closely with product owners and software developers to move projects from idea to integration.
- Communicate with clients the key elements that govern the model.
Essential Requirements:
- A postgraduate qualification in Data Science, Machine Learning, Statistics, Mathematics or a closely related quantitative field.
- 3+ years of working experience or a PhD in a quantitative field.
- Experience with various supervised/unsupervised/reinforcement learning methodologies (e.g. Neural Networks, Random Forests, GBMs, SVMs etc.).
- Advanced Python (e.g. Numpy, Pandas, TensorFlow, Scikit-Learn, Matplotlib, Keras, PyTorch SciPy etc.) and SQL programming skills.
- A good understanding of betting concepts and markets.
Desirable Requirements:
- Experience with object-oriented programming (C# or Java).
- Experience with Big Data tools (e.g. Apache Hadoop, MongoDB, Cassandra etc.).
- Experience with version control platforms (e.g. GitHub, Gitlab, Bitbucket etc.).
- Experience with Jira and Confluence.
Personal Requirements:
- Fluent in English (written and spoken).
- You must have a strong work ethic and outstanding interpersonal skills.
- You must be self-motivated, a team-player and a creative thinker.
Πληροφορική
Hybrid
Permanent
Full Time
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