Data Science Consultant - Middle East

Qualifications

To be successful in your application, you must...

• You have a training in Engineering School or a high-level training in the field of Data Science, statistical engineering, and econometrics, and you ideally justify a first experience in Big Data or Data Science (internship or 1st job).
• You have an excellent level in statistics and quantitative analysis (theoretical and practical knowledge, ease of understanding models and applying them).
• High capabilities in framing machine learning problems.
• Strong business acumen, as well as the ability to communicate findings, and mine vast amounts of data for useful insights.
• Proficiency in at least 2 of the following: Python, R, SQL.
• Solid foundation in scripting languages like ​​(Python, Perl, JS, bash) or compiled (C ++, Java) and/or have experience in environments UNIX / LINUX.
• You want to get involved and quickly take responsibility for high added value missions within a dynamic structure.
• You have the ability to work in a team, an open mind, a sense of analysis and you want to join a motivating professional environment where you share our values ​​of excellence, entrepreneurship, innovation, the culture of sharing, benevolence, personal / professional life balance.

and possess Expertise in some or all of the following:

• Data cleaning, manipulation and pre-processing, exploratory analysis, feature engineering and machine learning libraries like pandas, numpy, scipy, regex, matplotlib, seaborn, statsmodels , scikit-learn, xgboost, and nltk, genism or spacy.Supervised Learning: Regression (simple, multivariate) and Classification (binary, multi-class, multi-label).
• Unsupervised Learning: Clustering (customer segmentation, cluster and community detection) and Dimensionality Reduction (PCA, LDA, TruncatedSVD, NNMF, etc.).
• Recommender Systems: Collaborative Filtering, Content Based and Matrix Factorization Methods.
• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
• Natural Language Processing: Text Preprocessing (Arabic & English), Word2Vec, TF-IDF, Text Classification (binary, multi-class, muli-label), Topic Modeling (LDA, PLSA, Matrix Factorization Methods) and Text Similarity Scores.
• Computer Vision: Image Processing, Data Augmentation, Image Classification, Object Detection, and Semantic Segmentation.
• Deep Learning Frameworks like Pytorch, Tensorflow or Keras.
• Statistical Hypothesis Testing using respective libraries.
• Dealing with numerical, categorical, text and date machine learning feature engineering.
• Dynamic visualization including RShiny or Dash Python
• Familiarity with Business Intelligence visualization tools like Power BI and Tableau is a plus.

Additional information

Sia Partners is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.