The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. Must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.
- You will help create analytical solutions that range from developing and delivering code and models, to digging for meaningful insights in your results, and translating them into actionable plans for our clients.
- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
- You will shape solutions tailored to the needs of our clients, maximizing programming languages (e.g., R, Python), tech platforms, and disruptive analytics methodologies (e.g., Causal Inference, Bayesian Optimization, Geospatial Analytics, Natural Language Processing) as part of our tech-agnostic firm
- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques.
- Develop custom data models and algorithms to apply to data sets.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Develop processes and tools to monitor and analyze model performance and data accuracy.
- Present information using data visualization techniques
- 7-9 years of experience in data analytics and machine learning
- Experience using statistical computer languages (R, Python, SLQ, etc.)
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
- Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
- Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
- Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
- Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
- Experience in visualizing data using Python, R, or BI tools
- At least one certificate in this field is a must.
- Bachelor’s degree in Statistics, Mathematics, or Computer Science. Master’s or PHD is a great plus
- Fluent in English & Arabic
- Microsoft Certified: Azure Data Scientist Associate
- SAS Certified AI & Machine Learning Professional
- Tensorflow Developer Certificate
- IBM Data Science Professional Certificate
- Dell EMC Data Science Track (EMCDS)
- Offered Salary:
- Career Level: