Data Scientist (H/F)-Maroc

Data Scientist (H/F)-Maroc

Job details

Data Scientist (H/F)-Maroc
Contrat à Durée Indéterminée



Founded in Paris in 1997, our partner is an international firm dedicated to improving the economic, social and environmental performance of organisations.

Its consultants and technical experts provide concrete solutions that contribute to the sustainable progress of its clients.

The Group has over 2,300 employees in 13 countries, with 660

employees in Morocco, stands out for its unique positioning and high added value in the fields of innovation financing, ecological transition and improving the operational performance of companies.

At the centre of a data-driven eco-system, the Data team is in a position to drive the group's digital transformation.

In this context, Anywr is looking for Data Scientists (M/F) in Morocco.


  • Take charge of the implementation of various data science projects and participate in the success of our clients in many sectors (health, industry, communications, financial services, etc.).
  • Framing and formalising the client's needs, whether expressed or not.
  • Search for the most appropriate scientific approach to the problem.
  • Participate in the automatic extraction and management of massive data, structured or not.
  • Carry out statistical analyses and transform data.
  • Build predictive models and evaluate their performance.
  • Contribute to the production of algorithms and the industrialisation of developments.
  • Restore and enhance results with data visualisation tools.
  • Participation in the animation of the collaborator's domain (events, presentations,) and in the development strategy of the team.
  • Identify the needs and issues of the business units.
  • Define a statistical model that addresses the problem.
  • Build analytical tools to collect company data.
  • Sourcing and gathering all the structured and unstructured data sources needed for the analysis.
  • Organise, study and synthesise these data sources into usable results.
  • Building algorithms to improve search and targeting results.
  • Development of predictive models to anticipate changes in business data and trends.
  • Modeling behaviours and extracting new user uses.
  • Contribute to the production of algorithms and the industrialisation of developments.
  • Be responsible for the delivered solutions and their compliance with the client's expectations.
  • Contribute to the technology watch on Data Science and Big Data topics and supervise less experienced staff.


Years of experience From 3 years experience

Formation Bachelor's degree or equivalent in statistical analysis and computer programming or a university with a major in Data Science, Statistics or Applied Mathematics.

Certifications Statistics/Big Data/Machine Learning (would be a plus)

Technical skills :

  • Knowledge of statistics and machine learning;
  • Mastery of analytical modelling tools, decision trees and neural networks (logistic regression, linear regression, etc.) and of Feature Engineering.
  • Mastery of Technologies and Models: XGBoost, TensorFlow, Random Forest, SVM, etc.
  • Ability to produce supervised and unsupervised models.
  • Master of SMOTE "the Synthetic Minority Over-sampling Technique".
  • Ability to analyse and extract insights from structured (deep knowledge of SQL) and unstructured data.
  • To be able to present the results of the models: Lift curve, Roc- AUC, F1 Score, Recall, Accuracy, Confusion Matrix, etc.
  • Understanding of linear algebra and statistics.
  • Development experience to extract and query data (Python, R, Spark, Java).

Behavioural competencies :

  • Intellectual curiosity, initiative, proactivity.
  • Organisational skills.
  • Autonomous, good interpersonal skills, facilitator.
  • Excellent written and oral communication skills.

  • Attractive package with numerous social benefits (medical agreements, leisure activities, etc.);
  • International environment and start-up spirit in a large group;
  • Continuous learning environment;
  • Support throughout your career (career development path, internal and international development opportunities, etc.);
  • Seminars, team-buildings, team outings;
  • Opportunity to get involved in CSR projects;