Job Description

This role is for a 6 month internship Minimum as part of the data science team for PhD students in their penultimate year of graduation. Data Scientists at Careem are part of a team that's leading the next wave of enablement at a whole new scale. We develop descriptive and predictive models as well as run extensive data analyses on millions of customer transactions supported by a cutting edge data platform to unlock big opportunities that simplify lives of people through reliable transportation. Some of the problems the data science team works on are:

• Relevance and recommendation engine according to customer behaviour
• Dynamic pricing optimization
• Optimal dispatching
• Fraud detection and prevention
• ETA prediction
• Location search optimization

As part of this team, you’ll be working on some or all of the below:

• Implementing scalable machine learning algorithms that will be used in production on big data.
• Design and run randomized controlled experiments, analyze the resulting data and communicate results with other teams.
• Embarking on exploratory data analysis projects to achieve better understanding of phenomena as well as to discover untapped areas of growth and optimization.
• Answering complex analytic questions from big data sets to help Careem shape its products and services in a better way.
• Interpreting results of your analysis, validating their approach, and learning to monitor, analyze, and iterate to continuously improve.
• Engaging with peer stakeholders to produce clear, compelling, actionable insights that influence product and service improvements that will impact millions of customers.

What we’re looking for

Successful candidates will ideally exhibit and be able to demonstrate most of the below requirements.

• Must be in the penultimate year of graduation of a PhD in Computer Science, Mathematics, Statistics, Applied Sciences such as Physics or other quant-focused fields.
• Proficiency using one or more programming or scripting language to work with data (Python is a preferred language).
• Experience and/or coursework performing data analysis and applying statistics working with tools (e.g., R, MATLAB, AMPL, or SAS).
• Experience and/or coursework with business intelligence and visualization tools (Tableau is a preferred option) along with geospatial data processing skills.
• Experience and/or coursework applying ML to a type of data, including the application of ML algorithms on large scale data sets, and understanding of various ML algorithms and evaluations techniques.
• Hands on experience in development of deep / machine learning algorithms in PyTorch/ TensorFlow for computer vision / speech / natural language processing applications.
• Hands-on experience with big data processing.
• Experience in building industrial machine / deep learning systems.
• Passion to learn from your peers, manager, and other stakeholders in the Data Science and AI domain.
• Ability to interact with peers and stakeholders to drive product and business impact.
• Strong interpersonal and communications skills.