16 set - Torino
reale group
Objective:
Dato l'elevato interesse per questa posizione, la preghiamo di candidarsi tempestivamente se il suo profilo è in linea con il ruolo.
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- Works with data scientist, data engineer and data architect in order to authomatize, optimize and scale data products to ensure the industrialization and the performance of algorithms.
Responsibilities:
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- Works with stakeholders to formulate code approaches to solve problems using algorithms and data sources in context of customer, engineering, and business needs.
- Will use data exploration techniques to discover new opportunities or to find the best performance.
- Will interpret the results of analyses, validate approaches, and learn to monitor, analyze, and iterate to continuously improve the data product.
- Will engage with stakeholders to produce clear, compelling, and actionable insights that influence product and service improvements that will impact customers.
- Will also engage in the peer review process and act on feedback while learning innovative methods, algorithms, and tools to increase the impact and applicability of the data product.
- Will participate together with the DevOps team in choosing the best operational architecture.
- Will monitor the performance of ML models and implement the best technological solution within the operational architecture.
Qualifications:
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- Degree in Computer Science, Statistics, Mathematics, Economics, or similar.
- 2+ year of engineering experience using large data systems on SQL, Hadoop, Spark, etc.
- 2+ year of experience using one or more programming or scripting language like Python, Scala, or C# to work with data.
- 2+- year of experience using tools like Python, R, MATLAB, AMPL, SAS, or other relevant data science tools/environments.
- Experience with development tools like DevOps.
- Experience with data integration tool like Azure Data Factory and Azure Mapping Dataflow
- Experience with data transformation tool like Azure Databricks
- Experience with machine learning tool like Azure Machine Learning
- Experience with deploying tool like Dockers and Kubernetes
- Familiarity with data visualization tool like PowerBI
- Fluent written and spoken English.
Knowledge and experience with key data science areas such as machine learning, deep learning, anomaly detection, predictive analysis, text analysis, exploratory data analysis, and other areas of data science:
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- Experience performing data analysis including applying statistics.
- Ability in verbal and written communication skills presenting to large and small audiences.
- Ability to interact with peers and stakeholders to define and drive product and business impact. xysqume
- Master in Artificial Intelligence will be preferred.
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