About the job

Objective:

Works with data scientist, data engineer and data architect to automatize, optimize and scale data products to ensure the industrialization and the performance of algorithms.

Responsibilities:

  • 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, analyse, and iterate to continuously improve and ensure the data product are scalable.
  • 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.
  • Will have a strong relationship with the infrastructure team and develop using HTTP API logic in frameworks such as Lambda architecture.

 

Qualifications:

  • 5+ years of engineering experience using large data systems on SQL, PySpark, Spark, etc.
  • 5+ years of experience using one or more programming or scripting language like Python, Scala, PySpark or C# to work with data.
  • 5+ years of experience using tools like Python, R, MATLAB, AMPL, SAS, and other relevant data science tools/environments. (Jupyter Notebook)
  • 5+ years of experience developing AI and ML pipelines for continuous operation, feedback and monitoring of ML models leveraging best practices from the CI/CD automation; and DevOps principles
  • 2+ years of prior experience implementing HTTP REST APIs.
  • 2+ years of experience working in Azure Cloud
  • Be familiar with ML algorithms, AI use cases and applications.
  • Have knowledge about data engineering concepts, tools and automation processes (DataOps) since data pipelines and architectures provide the base for building AI solutions as all-in-one Databricks

 

Skills and Competencies:

  • Behavioural skills:
  • Strong collaboration skills
  • Objective Oriented
  • Accountable; takes ownership and pride in their work
  • Flexibility and adaptation to changing environments.
  • Ability to work in an agile scrum project team
  • Customer Orientation.
  • Complex problem-solving and analytical skills
  • Strong written and verbal communication skills
  • Be able to explain data product process to software developers
  • Continuous improvement and creativity.
  • Passion to learn world class techniques and tools.
  • Ability to multi-task, prioritize and be detail-oriented
  • Other requirements:
  • Degree in Computer Science, Statistics, Mathematics, Economics, or similar.
  • Master in Artificial Intelligence will be preferred.
  • Fluent written and spoken English. (Level C1)
  • Knowledge of the insurance business and its business processes in all its areas (nice to have)

 

Modalità di lavoro: ibrida Рufficio Torino o Milano + 12gg di smartworking/mese

La ricerca √® rivolta ai candidati ambosessi (l.903/77). Ti preghiamo di leggere l’Informatica Privacy ai sensi dell’Art. 13 del Regolamento (UE) 2016/679 sulla protezione dei dati (GDPR).

Tagged as: C++, MATLAB, PySpark, Python

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