Data Scientist

April 3

Apply Now
ekar logo

ekar

The Middle East's First and Largest Self-drive Personal Mobility Company.

Self Drive • Car Subscription • Carshare • Mobility • Transportation

51 - 200

💰 $17.5M Series B on 2019-11

Description

• Analyzing large datasets to extract actionable insights that could influence the company's business strategies. • Developing predictive models to forecast rental demands, customer preferences, and pricing trends. • Use machine learning models to build vehicle recommendation systems • Collaborating with cross-functional teams to understand data needs and deliver comprehensive analytical solutions. • Implementing machine learning algorithms to optimize the user experience, such as personalized recommendations and dynamic pricing models. • Monitoring and evaluating the performance of data-driven systems in real-time to ensure they are delivering optimal results. • Continuously exploring new data sources and analytics techniques to keep the company at the forefront of the industry.

Requirements

• Proficiency in Python/R, SQL, and statistical software. • Experience with machine learning, deep learning, and algorithm development. • Knowledge of data visualization tools. • Strong problem-solving and analytical skills. • Excellent communication and presentation abilities. • Proven experience as a Data Scientist, preferably in the tech or automotive sector. • Experience handling large data sets and conducting complex quantitative analyses. • A degree in Data Science, Mathematics, Economics, Computer Science, or a related field. Masters or Ph.D. preferred

Benefits

• Proficiency in Python/R, SQL, and statistical software. • Experience with machine learning, deep learning, and algorithm development. • Knowledge of data visualization tools. • Strong problem-solving and analytical skills. • Excellent communication and presentation abilities. • Proven experience as a Data Scientist, preferably in the tech or automotive sector. • Experience handling large data sets and conducting complex quantitative analyses. • A degree in Data Science, Mathematics, Economics, Computer Science, or a related field. Masters or Ph.D. preferred

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