Dear Students,
below an interesting job position for Data Scientists.
For further info write an email to rinaldi@math.unipd.it.
Cheers,
Francesco Rinaldi
*Key responsabilities of the role will include:*
- *Uses advanced analytics methods to extract value from business data*
- *Performs large-scale experimentation and builds data-driven models to
answer business questions*
- *Creates hypotheses and experiments to identify hidden relationships
and construct new analytics methods*
- *Researches bleeding-edge techniques and tools in machine
learning/deep learning/artificial intelligence*
- *Determines requirements that will be used to train and evolve deep
learning models and algorithms*
- *Articulates a vision and roadmap for the exploitation of data as a
valued corporate asset*
- *Visualizes information and develops reports on results of data
analysis*
- *Influences product teams through presentation of data-based
recommendations*
- *Spreads best practices to analytics and product teams and implements
new tools to make data analysis more efficient*
*Our ideal candidate will meet the following requirements:*
*Must have*
- *Bachelor Degree in a highly quantitative field (Computer Science,
Machine Learning, Operational Research, Statistics, Mathematics, etc.) and
Master's or PhD in Statistics, Applied Math, Operations Research,
Economics, or a related quantitative field*
- *At least three years of working experience in a research science,
machine learning, or data scientist role with a track record of complex
business problems solved leveraging both structured and unstructured data
sources*
- *Strong knowledge of Python and its main data processing and modeling
libraries (Numpy, Pandas, Scikit-learn, XGBoost)*
- *Good knowledge of Deep Learning models and frameworks (Keras,
TensorFlow, PyTorch,..)*
*Soft skills*
- *Ability to understand business problems and distill informal
requirements into analytics problems*
- *Ability to interact, communicate and present complex results to
technical and non-technical audiences within multiple levels of the
organization*
- *Ability to self-motivate, prioritizing needs, and delivering results
in a complex environment with ambiguity and minimal supervision*
- *Willingness to l**earn new technological, complex topics and to
continuously challenge itself*