Data Scientist - Excel/R/Python - Automotive

We ask the candidate to:

- master in Excel / R / Python

- know (at least) master the development environments: R-Studio, IPython Notebook, Jupyter, Wakari, Zeppelin

- know the main principles of Big Data

- know the main tools Big Data: unstructured database (Mongo DB, Cassandra) and the tools to request and exploit them (Hadoop, Spark)

- know a maximum and master certain statistical methodologies among:

- Probability / density laws (normal, Weibull, quartile, mean, standard deviation, unimodality, ...) and law of the mean

- Confidence intervals

- Risks of first species and second species (alpha and beta).

- Hypothesis tests and test power

- Design concepts (number of measurements to be carried out)

- Analysis of variance: decomposition of the variability for the measurement or for the process for the evaluation of the uncertainties

- The strategy of experiential plans vs. OneFactor At Time.

- Capability in industry (Cp / Cpk, leakage rate)

- Notions of risks

Keerthi, S