Data Scientist
Full Time
full time
31 Dec 1969
Milan
Verified by Turrior
Content + Source + Freshness • 12 Dec 2025 • 95% confidence
80 / 100
Offer value
High value due to the growing demand for data science skills and the ability to impact key business decisions.
- Significant opportunities within data science sector
- Ability to drive impactful business decisions
- Requires strong analytical and technical skills
Pros
- Opportunities to work with big data and advanced analytics
- High demand for data science skills across industries
- Ability to influence decision-making processes
Cons
- Complex skill set may limit candidate pool
- Requires significant experience with specific technologies
- Fast-paced pressure to deliver results
Who it's for
Junior to Mid Level • On-site
Good fit
- Data professionals with machine learning experience
- Individuals with analytical backgrounds
- Candidates interested in telecom data applications
Not recommended for
- Beginners without data science knowledge
- Those uninterested in analytics-focused roles
- Individuals seeking strictly non-technical jobs
Motivation fit
Desire to leverage data for business advancementsInterest in machine learning and statistical analysisWillingness to work on dynamic projects
Key skills
Data analysis and statistical modelingProficiency in programming languages (Python, SQL)Ability to implement machine learning algorithms
Score: 80/100 AI verified analysis
About the job
Key accountabilities and decision ownership : Identification of data science / big data / analytics use cases for Network Operations and architectural High Level Design Choice and implementation of the best machine learning algorithm suited to the use case Industrialization of the use cases on Cloudera, Openshift/Kubernetes or on AWS/Google cloud environments, with the support of data engineers Technical leadership in analysis and data management domains Data-driven evaluation of vendor product adoption Experience in Machine Learning SW development and data analysis Experience in designing and implementing use cases over big data architectures involving massive data volume, also under real-time constraints Knowledge of pros and cons of existing data storage technologies (relational DB, Big Data Frameworks, no-SQL DB on cloud and on prem) Degree in Computer Science, Maths, Engineering or equivalent Junior Profile with Experience in similar position (Max 2 years) SQL, Python (Pandas, Tensorflow, Scikit-learn, and main other ML libs), Pyspark and SW development capabilities Machine learning algorithms knowledge (NLP, Neural Networks., Random Forest, SVM, Anomaly Detection especially on time series, Gradient Boost and all other main ML models both supervised and unsupervised) Knowledge of deployment best practices and DevOps pipeline Excellent analytics and mathematics skills Professional English (spoken and written)
