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Datascience Consultant

Genève, Suisse

CDI - Temps plein

Salaire (brut annuel) : 120 000 - 145 000 CHF


Perfect knowledge of at least one language such as Python, R or Scala -
Knowledge of DataScience libraries on Python (e.g. Scikit learn, panda) R (e.g. factominer, ggplot2), Spark (Mllib)
Fluency in French and English (verbal & written)
Excellent communication skills (to be client facing)
He/She participates under the supervision of a Senior or Expert Data Scientist in several phases of the implementation of a Data Science project:
data preparation, analysis, choice of algorithms to be implemented, their programming, interpretation of results, production, through design and development using data manipulation languages
SQL, Hive, Impala, R, Python, Scala, etc .... ) and Data Science software (KNIME, Dataiku, H2O, Alteryx, SAS, SPSS, SAP Predictive Analytics, Dell Statistica, SPAD, etc ....)

The Data Scientist is capable of handling a large quantity of databases and sources, whatever their format (RDBMS, Hadoop), implementing the necessary algorithms, taking stock of the results obtained, and ensuring interaction with the client on the results obtained.

His/her mindset is strongly oriented towards problem solving, team spirit, and sharing knowledge with the rest of the team. With a passionate temperament, he/she plays a driving and major role in the team in which he/she intervenes.

Main activities :
- Actively participates in the technical and functional analysis of the client's needs, expectations and the functioning of the existing system in order to draft the functional and technical specifications of the chosen solution, actively participates in client workshops.
- Participates in the general and detailed technical design of the target solution
- Participates in the audit of the quality of client data
- Writes or supervises and adapts extraction notes (extraction of customer data for analysis)
- Writes or supervises data analysis reports
- Writes or corrects client interview reports
- Participates in the integration process of the various elements of the solution according to the established specifications
- Implements methods (in particular CRISP: Cross Reference Industry Standard Process for Data Science)
- Supervise and participate in the integration of data in the Data Hub
- Supervises and implements technical and integration tests in order to qualify and correct anomalies
- Participate in the installation of the solution and the training of the users and follow up with the client throughout the engagement
- Actively participates in the drafting of user documents and monitoring of achievements
- Carry out the unit progress monitoring including the estimation of its remaining production and communicate it to his manager allowing him to have the necessary visibility in order to alert in case of delays or other dysfunctions
- Carry out the programming of the algorithms using different languages and Data Science tools
- Participates in the interpretation of results and the presentation of these results to clients
- Proactively proposes solutions to problems encountered, whether technical, methodological or concerning the data
Must apply the quality approach in the performance of his/her tasks and throughout the projects, particularly when delivering the data to the client


Diploma: Bac+5 level in Business Intelligence, Statistics, Machine Learning, Data Science, Data Mining, Master 2 in Statistics, Machine Learning, Data Science or Artificial Intelligence.

- Equivalent Mooc certifications (Coursera, Edx, Udacity, Udemy) possible.

- Very strong foundation in statistics required

- Perfect knowledge of at least one language such as Python, R or Scala

- Knowledge of DataScience libraries on Python (e.g. Scikit learn, panda) R (e.g. factominer, ggplot2), Spark (Mllib)

- Knowledge of Hadoop and Spark architectures is an important plus

- Able to work with both supervised and unsupervised methods

Experience: 2 years as a Data Engineer or Junior Data Scientist on at least 2 different assignments

- Fluency in French and English (verbal & written)

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